Interval type-2 fuzzy neural networks(IT2FNNs)can be seen as the hybridization of interval type-2 fuzzy systems(IT2FSs) and neural networks(NNs). Thus, they naturally inherit the merits of both IT2 FSs and NNs. Althou...Interval type-2 fuzzy neural networks(IT2FNNs)can be seen as the hybridization of interval type-2 fuzzy systems(IT2FSs) and neural networks(NNs). Thus, they naturally inherit the merits of both IT2 FSs and NNs. Although IT2 FNNs have more advantages in processing uncertain, incomplete, or imprecise information compared to their type-1 counterparts, a large number of parameters need to be tuned in the IT2 FNNs,which increases the difficulties of their design. In this paper,big bang-big crunch(BBBC) optimization and particle swarm optimization(PSO) are applied in the parameter optimization for Takagi-Sugeno-Kang(TSK) type IT2 FNNs. The employment of the BBBC and PSO strategies can eliminate the need of backpropagation computation. The computing problem is converted to a simple feed-forward IT2 FNNs learning. The adoption of the BBBC or the PSO will not only simplify the design of the IT2 FNNs, but will also increase identification accuracy when compared with present methods. The proposed optimization based strategies are tested with three types of interval type-2 fuzzy membership functions(IT2FMFs) and deployed on three typical identification models. Simulation results certify the effectiveness of the proposed parameter optimization methods for the IT2 FNNs.展开更多
Wireless information and powered transfer networks(WIPT) has recently been implemented in 5th generation wireless networks. In this paper, we consider half-duplex relaying system in which the energy constrained relay ...Wireless information and powered transfer networks(WIPT) has recently been implemented in 5th generation wireless networks. In this paper, we consider half-duplex relaying system in which the energy constrained relay node collects energy via radio frequency(RF) signals from the surrounding resources. Regarding energy harvesting protocol, we propose power time switching-based relaying(PTSR) architecture for both amplify-and-forward(AF) and decode-and-forward(DF). Especially, we reveal the analytical expressions of achievable throughput, ergodic capacity and energy-efficient in case of imperfect channel state information(CSI) for both AF and DF network. Through numerical analysis, we analyse the throughput performance, energy-efficient and ergodic capacity for different parameters, including power splitting ratio and energy harvesting time. Moreover, we also depict the performance comparison between AF and DF network with perfect and imperfect CSI. The results in numerical analysis reveal that the result of AF relaying network is less significant than DF relaying network in the various scenarios.展开更多
Radial Basis Function Neural Network(RBFNN)ensembles have long suffered from non-efficient training,where incorrect parameter settings can be computationally disastrous.This paper examines different evolutionary algor...Radial Basis Function Neural Network(RBFNN)ensembles have long suffered from non-efficient training,where incorrect parameter settings can be computationally disastrous.This paper examines different evolutionary algorithms for training the Symbolic Radial Basis Function Neural Network(SRBFNN)through the behavior’s integration of satisfiability programming.Inspired by evolutionary algorithms,which can iteratively find the nearoptimal solution,different Evolutionary Algorithms(EAs)were designed to optimize the producer output weight of the SRBFNN that corresponds to the embedded logic programming 2Satisfiability representation(SRBFNN-2SAT).The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms,including Genetic Algorithm(GA),Evolution Strategy Algorithm(ES),Differential Evolution Algorithm(DE),and Evolutionary Programming Algorithm(EP).Each of these methods is presented in the steps in the flowchart form which can be used for its straightforward implementation in any programming language.With the use of SRBFNN-2SAT,a training method based on these algorithms has been presented,then training has been compared among algorithms,which were applied in Microsoft Visual C++software using multiple metrics of performance,including Mean Absolute Relative Error(MARE),Root Mean Square Error(RMSE),Mean Absolute Percentage Error(MAPE),Mean Bias Error(MBE),Systematic Error(SD),Schwarz Bayesian Criterion(SBC),and Central Process Unit time(CPU time).Based on the results,the EP algorithm achieved a higher training rate and simple structure compared with the rest of the algorithms.It has been confirmed that the EP algorithm is quite effective in training and obtaining the best output weight,accompanied by the slightest iteration error,which minimizes the objective function of SRBFNN-2SAT.展开更多
The computational complexity of resource allocation processes,in cognitive radio networks(CRNs),is a major issue to be managed.Furthermore,the complicated solution of the optimal algorithm for handling resource alloca...The computational complexity of resource allocation processes,in cognitive radio networks(CRNs),is a major issue to be managed.Furthermore,the complicated solution of the optimal algorithm for handling resource allocation in CRNs makes it unsuitable to adopt in real-world applications where both cognitive users,CRs,and primary users,PUs,exist in the identical geographical area.Hence,this work offers a primarily price-based power algorithm to reduce computational complexity in uplink scenarioswhile limiting interference to PUs to allowable threshold.Hence,this paper,compared to other frameworks proposed in the literature,proposes a two-step approach to reduce the complexity of the proposed mathematical model.In the first step,the subcarriers are assigned to the users of the CRN,while the cost function includes a pricing scheme to provide better power control algorithm with improved reliability proposed in the second stage.The main contribution of this paper is to lessen the complexity of the proposed algorithm and to offer flexibility in controlling the interference produced to the users of the primary networks,which has been achieved by including a pricing function in the proposed cost function.Finally,the performance of the proposed power and subcarrier algorithm is confirmed for orthogonal frequency-division multiplexing(OFDM).Simulation results prove that the performance of the proposed algorithm is better than other algorithms,albeit with a lesser complexity of O(NM)+O(Nlog(N)).展开更多
In this paper, the system performance of a decode-and-forward(DF) full-duplex(FD) adaptive relaying network over the Rician fading environment is proposed, analyzed and demonstrated. In the first stage, the system is ...In this paper, the system performance of a decode-and-forward(DF) full-duplex(FD) adaptive relaying network over the Rician fading environment is proposed, analyzed and demonstrated. In the first stage, the system is presented with the energy harvesting and information transmission processes. After that, the analytical expressions of the achievable throughput, the outage probability, and symbol error ratio(SER) were proposed, analyzed and demonstrated. Finally, the analytical results are also demonstrated by Monte-Carlo simulation in comparison with the closed-form expressions in the influence of the key system parameters. The results show that the analytical and simulated results match for all possible parameter values.展开更多
This paper studies the dynamics of a new fractional-order discrete system based on the Caputo-like difference operator.This is the first study to explore a three-dimensional fractional-order discrete chaotic system wi...This paper studies the dynamics of a new fractional-order discrete system based on the Caputo-like difference operator.This is the first study to explore a three-dimensional fractional-order discrete chaotic system without equilibrium.Through phase portrait,bifurcation diagrams,and largest Lyapunov exponents,it is shown that the proposed fractional-order discrete system exhibits a range of different dynamical behaviors.Also,different tests are used to confirm the existence of chaos,such as 0-1 test and C0 complexity.In addition,the quantification of the level of chaos in the new fractional-order discrete system is measured by the approximate entropy technique.Furthermore,based on the fractional linearization method,a one-dimensional controller to stabilize the new system is proposed.Numerical results are presented to validate the findings of the paper.展开更多
Railway transportation system is a critical sector where design methods and techniques are defined by international standards in order to reduce possible risks to an acceptable minimum level. CENELEC 50128 strongly re...Railway transportation system is a critical sector where design methods and techniques are defined by international standards in order to reduce possible risks to an acceptable minimum level. CENELEC 50128 strongly recommends the utilization of finite state machines during system modelling stage and formal proof methods during the verification and testing stages of control algorithms. Due to the high importance of interlocking table at the design state of a signalization system, the modelling and verification of interlocking tables are examined in this work. For this purpose,abstract state machines are used as a modelling tool. The developed models have been performed in a generalized structure such that the model control can be done automatically for the interlocking systems. In this study, Nu SMV is used at the verification state. Also, the consistency of the developed models has been supervised through fault injection.The developed models and software components are applied on a real railway station operated by Metro Istanbul Co.展开更多
As the extension of the linear inverted pendulum(LIP) and planar inverted pendulum(PIP), this paper proposes a novel spatial inverted pendulum(SIP). The SIP is the most general inverted pendulum(IP) than any existing ...As the extension of the linear inverted pendulum(LIP) and planar inverted pendulum(PIP), this paper proposes a novel spatial inverted pendulum(SIP). The SIP is the most general inverted pendulum(IP) than any existing IP. The model of the SIP is presented for the first time. The SIP inherits all the characteristics of the LIP and the PIP, which is a nonlinear,unstable and underactuated system. The SIP has five degrees of motion freedom and three control forces. Thus, it is a multipleinput and multiple-output(MIMO) system with nonlinear dynamics. To realize the spatial trajectory tracking of the SIP,the control structure with five PID controllers will be designed.The parameter tuning of the multiple PIDs is a challenging work for the proposed SIP model. To alleviate the difficulties of the parameter tuning for the multiple PID controllers, optimal PIDs can be achieved with the help of Big Bang – Big Crunch(BBBC) optimization. The BBBC algorithm can successfully optimize the parameters of the multiple PID controllers with high convergence speed. The optimization performance index of the BBBC algorithm is compared with that of the particle swarm optimization(PSO). Simulation results certify the rightness and effectiveness of the proposed control and optimization methods.展开更多
Fifth-generation(5G)cellular networks offer high transmission rates in dense urban environments.However,a massive deployment of small cells will be required to provide wide-area coverage,which leads to an increase in ...Fifth-generation(5G)cellular networks offer high transmission rates in dense urban environments.However,a massive deployment of small cells will be required to provide wide-area coverage,which leads to an increase in the number of handovers(HOs).Mobility management is an important issue that requires considerable attention in heterogeneous networks,where 5G ultra-dense small cells coexist with current fourth-generation(4G)networks.Although mobility robustness optimization(MRO)and load balancing optimization(LBO)functions have been introduced in the 3GPP standard to address HO problems,non-robust and nonoptimal algorithms for selecting appropriate HO control parameters(HCPs)still exist,and an optimal solution is subjected to compromise between LBO and MRO functions.Thus,HO decision algorithms become inefficient.This paper proposes a conflict resolution technique to address the contradiction between MRO and LBO functions.The proposed technique exploits received signal reference power(RSRP),cell load and user speed to adapt HO margin(HM)and time to trigger(TTT).Estimated HM and TTT depend on a weighting function and HO type which is represented by user status during mobility.The proposed technique is validated with other existing algorithms from the literature.Simulation results demonstrate that the proposed technique outperforms existing algorithms overall performance metrics.The proposed technique reduces the overall average HO ping-pong probability,HO failure rate and interruption time by more than 90%,46%and 58%,respectively,compared with the other schemes overall speed scenarios and simulation time.展开更多
In this paper we focus on the target capturing problem for a swarm of agents modelled as double integrators in any finite space dimension.Each agent knows the relative position of the target and has only an estimation...In this paper we focus on the target capturing problem for a swarm of agents modelled as double integrators in any finite space dimension.Each agent knows the relative position of the target and has only an estimation of its velocity and acceleration.Given that the estimation errors are bounded by some known values,it is possible to design a control law that ensures that agents enter a user-defined ellipsoidal ring around the moving target.Agents know the relative position of the other members whose distance is smaller than a common detection radius.Finally,in the case of no uncertainty about target data and homogeneous agents,we show how the swarm can reach a static configuration around the moving target.Some simulations are reported to show the effectiveness of the proposed strategy.展开更多
Mobile broadband(MBB)networks are expanding rapidly to deliver higher data speeds.The fifth-generation cellular network promises enhanced-MBB with high-speed data rates,low power connectivity,and ultralow latency vide...Mobile broadband(MBB)networks are expanding rapidly to deliver higher data speeds.The fifth-generation cellular network promises enhanced-MBB with high-speed data rates,low power connectivity,and ultralow latency video streaming.However,existing cellular networks are unable to perform well due to high latency and low bandwidth,which degrades the performance of various applications.As a result,monitoring and evaluation of the performance of these network-supported services is critical.Mobile network providers optimize and monitor their network performance to ensure the highest quality of service to their end-users.This paper proposes a Bayesian model to estimate the minimum opinion score(MOS)of video streaming services for any particular cellular network.The MOS is the most commonly used metric to assess the quality of experience.The proposed Bayesian model consists of several input data,namely,round-trip time,stalling load,and bite rates.It was examined and evaluated using several test data sizes with various performance metrics.Simulation results show the proposed Bayesian network achieved higher accuracy overall test data sizes than a neural network.The proposed Bayesian network obtained a remarkable overall accuracy of 90.36%and outperformed the neural network.展开更多
Intracavity absorption spectroscopy is a strikingly sensitive technique that has been integrated with a two-wavelength setup to develop a sensor for human breath.Various factors are considered in such a scenario,out o...Intracavity absorption spectroscopy is a strikingly sensitive technique that has been integrated with a two-wavelength setup to develop a sensor for human breath.Various factors are considered in such a scenario,out of which Relative Intensity Noise(RIN)has been exploited as an important parameter to characterize and calibrate the said setup.During the performance of an electrical based assessment arrangement which has been developed in the laboratory as an alternative to the expensive Agilent setup,the optical amplifier plays a pivotal role in its development and operation,along with other components and their significance.Therefore,the investigation and technical analysis of the amplifier in the system has been explored in detail.The algorithm developed for the automatic measurements of the system has been effectively deployed in terms of the laser’s performance.With this in perspective,a frequency dependent calibration has been pursued in depth with this scheme which enhances the sensor’s efficiency in terms of its sensitivity.In this way,our investigation helps us in a better understanding and implementation perspective of the proposed system,as the outcomes of our analysis adds to the precision and accuracy of the entire system.展开更多
Necessity of electricity access in remote area is the main reason for expanding decentralized energy system such as stand-alone power systems. The best electrical power supply must provide a constant magnitude and fre...Necessity of electricity access in remote area is the main reason for expanding decentralized energy system such as stand-alone power systems. The best electrical power supply must provide a constant magnitude and frequency voltage. Therefore, good power quality is an important factor for the reliable operation of electrical loads in a power system. However, the current drawn by most of electronic devices and non-linear loads are non-sinusoidal, which can result in a poor power quality, especially in off-grid power systems. Poor power quality is characterized by electrical disturbances such as transients, sags, swells, harmonics and even interruptions in the power supply. Off-grid power systems worldwide often struggle with system failures and equipment damage due to poor power quality. In this paper, MAT- LAB/Simulink is used to model and analyses power quality in an off-grid renewable energy system. The results show high voltage transient when the inductive loads were switched OFF. The voltage and current harmonics are also determined and compared for various types of loads.展开更多
Load Frequency Control (LFC) is one of power systems important requirements which maintain the zero steady-state errors in the frequency changing and restoring the natural frequency to its normal position. Many proble...Load Frequency Control (LFC) is one of power systems important requirements which maintain the zero steady-state errors in the frequency changing and restoring the natural frequency to its normal position. Many problems are subject to LFC such as suddenly large load or suddenly disconnecting generating unit by the protection device. In this paper, multi-area Frequency Control by using the combination of PSO and fuzzy logic control (FLC) technique. PSO optimization method is used to tuning the fuzzy controller input and output gains. Four of an interconnected electrical power system used as a testing the effectiveness of the proposed method compared to a conventional PI controller and scaled-fuzzy controller. The simulation result has been shown that the controller can generate the best dynamic response in multi-load conditions.展开更多
The evaluation of distortion diagnosis using Wavelet function for Electrocardiogram (ECG), Electroencephalogram (EEG) and Phonocardiography (PCG) is not novel. However, some of the technological and economic issues re...The evaluation of distortion diagnosis using Wavelet function for Electrocardiogram (ECG), Electroencephalogram (EEG) and Phonocardiography (PCG) is not novel. However, some of the technological and economic issues remain challenging. The work in this paper is focusing on the reduction of the noise interferences and analyzes different kinds of ECG signals. Furthermore, a physiological monitoring system with a programming model for the filtration of ECG is presented. Kaiser based Finite Impulse Response (FIR) filter is used for noise reduction and identification of R peaks based on Peak Detection Algorithm (PDA). Two approaches are implemented for detecting the R peaks;Amplitude Threshold Value (ATV) and Peak Prediction Technique (PPT). Daubechies wavelet transform is applied to analyze the ECG of driver under stress, arrhythmia and sudden cardiac arrest signals. From the obtained results, it was found that the PPT is an effective and efficient technique in detecting the R peaks compared to ATV.展开更多
Sugar is important in daily food intake since it is used as food preservative and sweetener.Therefore,is important to analyze the influence of sugar on the spectroscopic properties of the sample.Terahertz spectroscopy...Sugar is important in daily food intake since it is used as food preservative and sweetener.Therefore,is important to analyze the influence of sugar on the spectroscopic properties of the sample.Terahertz spectroscopy is proven to be useful and an efficient method for sugar detection as well as for future food quality industry.However,the lack of detection sensitivity in Terahertz Spectroscopy has prevented it from being used in a widespread spectroscopic analysis technology.In this paper,Frequency Selective Surface(FSS)using the Terahertz Spectroscopy Time Domain Spectrum(THz-TDS)which operates at terahertz frequency range has been demonstrated for application of sugar detection.The FSS is designed with a circle slot structure and has been optimized in line with the molecular resonance of glucose and fructose at different level concentration at 1.98 THz and 1.80 THz,respectively.Transmission magnitude of glucose and sucrose is inversely proportional with the level of sugar concentrations.The realization of the FSS structure is using electron beam lithography and wet etching technique.Results show that the FSS performance for glucose and sucrose reveal fair shifts in measured transmission magnitude from its original in CST by approximately 30%.The use of fabricated FSS with circle structure indicates that the concentration can be improved averagely at 25%for glucose and 13%for sucrose.Thus,it shows that the FSS circle structure combined with THz-TDS has the potential to become an alternative method for food sensing technology in the future.展开更多
Electrical transformers are vital components found virtually in most power-operated equipments. These transformers spontaneously radiate heat in both operation and steady-state mode. Should this thermal radiation inhe...Electrical transformers are vital components found virtually in most power-operated equipments. These transformers spontaneously radiate heat in both operation and steady-state mode. Should this thermal radiation inherent in transformers rises above allowable threshold a reduction in efficiency of operation occurs. In addition, this could cause other components in the system to malfunction. The aim of this work is to detect the remote causes of this undesirable thermal rise in transformers such as oil distribution transformers and ways to control this prevailing thermal problem. Oil transformers consist of these components: windings usually made of copper or aluminum conductor, the core normally made of silicon steel, the heat radiators, and the dielectric materials such as transformer oil, cellulose insulators and other peripherals. The Resistor-Inductor-Capacitor Thermal Network (RLCTN) model at architectural level identifies with these components to have ensemble operational mode as oil transformer. The Inductor represents the windings, the Resistor representing the core and the Capacitor represents the dielectrics. Thermography of transformer under various loading conditions was analyzed base on Infrared thermal gradient. Mathematical, experimental, and simulation results gotten through RLCTN with respect to time and thermal image analysis proved that the capacitance of the dielectric is inversely proportional to the thermal rise.展开更多
<span style="white-space:normal;">This paper studies the influence factors of atoms number (N) at temperature (T) and after annealing time (t) on the structure shape and the plastic deformation of Poly...<span style="white-space:normal;">This paper studies the influence factors of atoms number (N) at temperature (T) and after annealing time (t) on the structure shape and the plastic deformation of Polyethylene C</span><sub style="white-space:normal;">2</sub><span style="white-space:normal;">H</span><sub style="white-space:normal;">4</sub><span style="white-space:normal;"> (PE) by the Molecular Dynamics (MD) method with Dreading pair interaction, cyclic boundary conditions and plastic deformation of Polyethylene (PE) be done by stretching method according to the z-axis. The results of structure, plastic deformation of PE are analyzed through size (l), the total energy of the system (E</span><sub style="white-space:normal;">tot</sub><span style="white-space:normal;">), shape and associated energy (E</span><sub style="white-space:normal;">bond</sub><span style="white-space:normal;">), angular binding energy (E</span><sub style="white-space:normal;">angle</sub><span style="white-space:normal;">), energy E</span><sub style="white-space:normal;">dihedral</sub><span style="white-space:normal;">, interactive energy Vander Walls (E</span><sub style="white-space:normal;">non-bonding</sub><span style="white-space:normal;">). When increasing N, t leads to the number of structural units of Face-Centred Cubic (FCC), Body-Centered Cubic (BCC) and Hexagonal Close-Packed (HCP) increasing, but Amorphous (Amor) decreases while the angle between the atoms is a constant corresponding to 109.5</span>°<span style="white-space:normal;">. Besides, the length of the link (r) increases from r = 1.529 </span>Å<span style="white-space:normal;"> to r = 1.558 </span>Å<span style="white-space:normal;"> while the plastic deformation energy of PE gets an enormous change and the bonding angle at 109.27</span>°<span style="white-space:normal;">. The length of the link r = 1.529 </span>Å<span style="white-space:normal;"> and the size (l) of the PE material increase from l = 3.73 nm to l = 6.63 nm while the total energy of system (E</span><sub style="white-space:normal;">total</sub><span style="white-space:normal;">) decreases from E</span><sub style="white-space:normal;">total</sub><span style="white-space:normal;"> = <span style="white-space:nowrap;">−</span>1586 eV to E</span><sub style="white-space:normal;">total</sub><span style="white-space:normal;"> = <span style="white-space:nowrap;">−</span>7891 eV with the transition temperature is T = 103 K. Increasing the number of atoms leads to increasing the length of the link. The total energy E</span><sub style="white-space:normal;">total </sub><span style="white-space:normal;">of the system decreases, but the number of structural units in FCC, HCP, BCC and Amor increase, which leads to the length of the link increases, the E</span><sub style="white-space:normal;">total</sub><span style="white-space:normal;"> decreases, and there is a change in the plastic deformation characteristics of PE. In contrast, increasing T leads to the plastic deformation increases, and PE moves from the amorphous state to the liquid state. The obtained results are very significant for future experimental research.</span>展开更多
Artificial intelligence,machine learning and deep learning algorithms have been widely used for Maximum Power Point Tracking(MPPT)in solar systems.In the traditional MPPT strategies,following of worldwide Global Maxim...Artificial intelligence,machine learning and deep learning algorithms have been widely used for Maximum Power Point Tracking(MPPT)in solar systems.In the traditional MPPT strategies,following of worldwide Global Maximum Power Point(GMPP)under incomplete concealing conditions stay overwhelming assignment and tracks different nearby greatest power focuses under halfway concealing conditions.The advent of artificial intelligence in MPPT has guaranteed of accurate following of GMPP while expanding the significant performance and efficiency of MPPT under Partial Shading Conditions(PSC).Still the selection of an efficient learning based MPPT is complex because each model has its advantages and drawbacks.Recently,Meta-heuristic algorithm based Learning techniques have provided better tracking efficiency but still exhibit dull performances under PSC.This work represents an excellent optimization based on Spotted Hyena Enabled Reliable BAT(SHERB)learning models,SHERB-MPPT integrated with powerful extreme learning machines to identify the GMPP with fast convergence,low steady-state oscillations,and good tracking efficiency.Extensive testing using MATLAB-SIMULINK,with 50000 data combinations gathered under partial shade and normal settings.As a result of simulations,the proposed approach offers 99.7%tracking efficiency with a slower convergence speed.To demonstrate the predominance of the proposed system,we have compared the performance of the system with other hybrid MPPT learning models.Results proved that the proposed cross breed MPPT model had beaten different techniques in recognizing GMPP viably under fractional concealing conditions.展开更多
We propose a modified Fitzhugh-Nagumo neuron(MFNN) model. Based on this model, an integerorder MFNN system(case A) and a fractional-order MFNN system(case B) were investigated. In the presence of electromagnetic induc...We propose a modified Fitzhugh-Nagumo neuron(MFNN) model. Based on this model, an integerorder MFNN system(case A) and a fractional-order MFNN system(case B) were investigated. In the presence of electromagnetic induction and radiation, memductance and induction can show a variety of distributions. Fractionalorder magnetic flux can then be considered. Indeed, a fractional-order setting can be acceptable for non-uniform diffusion. In the case of an MFNN system with integer-order discontinuous magnetic flux, the system has chaotic and non-chaotic attractors. Dynamical analysis of the system shows the birth and death of period doubling, which is a sign of antimonotonicity. Such a behavior has not been studied previously in the dynamics of neurons. In an MFNN system with fractional-order discontinuous magnetic flux, different attractors such as chaotic and periodic attractors can be observed. However, there is no sign of antimonotonicity.展开更多
基金supported by the National Natural Science Foundation of China (61873079,51707050)
文摘Interval type-2 fuzzy neural networks(IT2FNNs)can be seen as the hybridization of interval type-2 fuzzy systems(IT2FSs) and neural networks(NNs). Thus, they naturally inherit the merits of both IT2 FSs and NNs. Although IT2 FNNs have more advantages in processing uncertain, incomplete, or imprecise information compared to their type-1 counterparts, a large number of parameters need to be tuned in the IT2 FNNs,which increases the difficulties of their design. In this paper,big bang-big crunch(BBBC) optimization and particle swarm optimization(PSO) are applied in the parameter optimization for Takagi-Sugeno-Kang(TSK) type IT2 FNNs. The employment of the BBBC and PSO strategies can eliminate the need of backpropagation computation. The computing problem is converted to a simple feed-forward IT2 FNNs learning. The adoption of the BBBC or the PSO will not only simplify the design of the IT2 FNNs, but will also increase identification accuracy when compared with present methods. The proposed optimization based strategies are tested with three types of interval type-2 fuzzy membership functions(IT2FMFs) and deployed on three typical identification models. Simulation results certify the effectiveness of the proposed parameter optimization methods for the IT2 FNNs.
文摘Wireless information and powered transfer networks(WIPT) has recently been implemented in 5th generation wireless networks. In this paper, we consider half-duplex relaying system in which the energy constrained relay node collects energy via radio frequency(RF) signals from the surrounding resources. Regarding energy harvesting protocol, we propose power time switching-based relaying(PTSR) architecture for both amplify-and-forward(AF) and decode-and-forward(DF). Especially, we reveal the analytical expressions of achievable throughput, ergodic capacity and energy-efficient in case of imperfect channel state information(CSI) for both AF and DF network. Through numerical analysis, we analyse the throughput performance, energy-efficient and ergodic capacity for different parameters, including power splitting ratio and energy harvesting time. Moreover, we also depict the performance comparison between AF and DF network with perfect and imperfect CSI. The results in numerical analysis reveal that the result of AF relaying network is less significant than DF relaying network in the various scenarios.
基金This work is supported by Ministry of Higher Education(MOHE)through Fundamental Research Grant Scheme(FRGS)(FRGS/1/2020/STG06/UTHM/03/7).
文摘Radial Basis Function Neural Network(RBFNN)ensembles have long suffered from non-efficient training,where incorrect parameter settings can be computationally disastrous.This paper examines different evolutionary algorithms for training the Symbolic Radial Basis Function Neural Network(SRBFNN)through the behavior’s integration of satisfiability programming.Inspired by evolutionary algorithms,which can iteratively find the nearoptimal solution,different Evolutionary Algorithms(EAs)were designed to optimize the producer output weight of the SRBFNN that corresponds to the embedded logic programming 2Satisfiability representation(SRBFNN-2SAT).The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms,including Genetic Algorithm(GA),Evolution Strategy Algorithm(ES),Differential Evolution Algorithm(DE),and Evolutionary Programming Algorithm(EP).Each of these methods is presented in the steps in the flowchart form which can be used for its straightforward implementation in any programming language.With the use of SRBFNN-2SAT,a training method based on these algorithms has been presented,then training has been compared among algorithms,which were applied in Microsoft Visual C++software using multiple metrics of performance,including Mean Absolute Relative Error(MARE),Root Mean Square Error(RMSE),Mean Absolute Percentage Error(MAPE),Mean Bias Error(MBE),Systematic Error(SD),Schwarz Bayesian Criterion(SBC),and Central Process Unit time(CPU time).Based on the results,the EP algorithm achieved a higher training rate and simple structure compared with the rest of the algorithms.It has been confirmed that the EP algorithm is quite effective in training and obtaining the best output weight,accompanied by the slightest iteration error,which minimizes the objective function of SRBFNN-2SAT.
基金Authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through Large Groups Project under Grant Number RGP.2/111/43supported in part by the Agencia Estatal de Investigación,Ministerio de Ciencia e Innovación(MCIN/AEI/10.13039/501100011033)+1 种基金the R+D+i Project under Grant PID2020-115323RB-C31in part by the Grant from the Spanish Ministry of Economic Affairs and Digital Transformation and the European Union-NextGenerationEU under Grant UNICO-5G I+D/AROMA3D-Hybrid TSI-063000-2021-71.
文摘The computational complexity of resource allocation processes,in cognitive radio networks(CRNs),is a major issue to be managed.Furthermore,the complicated solution of the optimal algorithm for handling resource allocation in CRNs makes it unsuitable to adopt in real-world applications where both cognitive users,CRs,and primary users,PUs,exist in the identical geographical area.Hence,this work offers a primarily price-based power algorithm to reduce computational complexity in uplink scenarioswhile limiting interference to PUs to allowable threshold.Hence,this paper,compared to other frameworks proposed in the literature,proposes a two-step approach to reduce the complexity of the proposed mathematical model.In the first step,the subcarriers are assigned to the users of the CRN,while the cost function includes a pricing scheme to provide better power control algorithm with improved reliability proposed in the second stage.The main contribution of this paper is to lessen the complexity of the proposed algorithm and to offer flexibility in controlling the interference produced to the users of the primary networks,which has been achieved by including a pricing function in the proposed cost function.Finally,the performance of the proposed power and subcarrier algorithm is confirmed for orthogonal frequency-division multiplexing(OFDM).Simulation results prove that the performance of the proposed algorithm is better than other algorithms,albeit with a lesser complexity of O(NM)+O(Nlog(N)).
文摘In this paper, the system performance of a decode-and-forward(DF) full-duplex(FD) adaptive relaying network over the Rician fading environment is proposed, analyzed and demonstrated. In the first stage, the system is presented with the energy harvesting and information transmission processes. After that, the analytical expressions of the achievable throughput, the outage probability, and symbol error ratio(SER) were proposed, analyzed and demonstrated. Finally, the analytical results are also demonstrated by Monte-Carlo simulation in comparison with the closed-form expressions in the influence of the key system parameters. The results show that the analytical and simulated results match for all possible parameter values.
基金The author Adel Ouannas was supported by the Directorate General for Scientific Research and Technological Development of Algeria.The author Shaher Momani was supported by Ajman University in UAE.
文摘This paper studies the dynamics of a new fractional-order discrete system based on the Caputo-like difference operator.This is the first study to explore a three-dimensional fractional-order discrete chaotic system without equilibrium.Through phase portrait,bifurcation diagrams,and largest Lyapunov exponents,it is shown that the proposed fractional-order discrete system exhibits a range of different dynamical behaviors.Also,different tests are used to confirm the existence of chaos,such as 0-1 test and C0 complexity.In addition,the quantification of the level of chaos in the new fractional-order discrete system is measured by the approximate entropy technique.Furthermore,based on the fractional linearization method,a one-dimensional controller to stabilize the new system is proposed.Numerical results are presented to validate the findings of the paper.
文摘Railway transportation system is a critical sector where design methods and techniques are defined by international standards in order to reduce possible risks to an acceptable minimum level. CENELEC 50128 strongly recommends the utilization of finite state machines during system modelling stage and formal proof methods during the verification and testing stages of control algorithms. Due to the high importance of interlocking table at the design state of a signalization system, the modelling and verification of interlocking tables are examined in this work. For this purpose,abstract state machines are used as a modelling tool. The developed models have been performed in a generalized structure such that the model control can be done automatically for the interlocking systems. In this study, Nu SMV is used at the verification state. Also, the consistency of the developed models has been supervised through fault injection.The developed models and software components are applied on a real railway station operated by Metro Istanbul Co.
基金supported by the National Natural Science Foundation of China(61873079)。
文摘As the extension of the linear inverted pendulum(LIP) and planar inverted pendulum(PIP), this paper proposes a novel spatial inverted pendulum(SIP). The SIP is the most general inverted pendulum(IP) than any existing IP. The model of the SIP is presented for the first time. The SIP inherits all the characteristics of the LIP and the PIP, which is a nonlinear,unstable and underactuated system. The SIP has five degrees of motion freedom and three control forces. Thus, it is a multipleinput and multiple-output(MIMO) system with nonlinear dynamics. To realize the spatial trajectory tracking of the SIP,the control structure with five PID controllers will be designed.The parameter tuning of the multiple PIDs is a challenging work for the proposed SIP model. To alleviate the difficulties of the parameter tuning for the multiple PID controllers, optimal PIDs can be achieved with the help of Big Bang – Big Crunch(BBBC) optimization. The BBBC algorithm can successfully optimize the parameters of the multiple PID controllers with high convergence speed. The optimization performance index of the BBBC algorithm is compared with that of the particle swarm optimization(PSO). Simulation results certify the rightness and effectiveness of the proposed control and optimization methods.
基金The research leading to these results has received funding from The Research Council(TRC)of the Sultanate of Oman under the Block Funding Program with agreement no.TRC/BFP/ASU/01/2019,and it was also supported in part by the Universiti Sains Islam Malaysia(USIM),Malaysia.
文摘Fifth-generation(5G)cellular networks offer high transmission rates in dense urban environments.However,a massive deployment of small cells will be required to provide wide-area coverage,which leads to an increase in the number of handovers(HOs).Mobility management is an important issue that requires considerable attention in heterogeneous networks,where 5G ultra-dense small cells coexist with current fourth-generation(4G)networks.Although mobility robustness optimization(MRO)and load balancing optimization(LBO)functions have been introduced in the 3GPP standard to address HO problems,non-robust and nonoptimal algorithms for selecting appropriate HO control parameters(HCPs)still exist,and an optimal solution is subjected to compromise between LBO and MRO functions.Thus,HO decision algorithms become inefficient.This paper proposes a conflict resolution technique to address the contradiction between MRO and LBO functions.The proposed technique exploits received signal reference power(RSRP),cell load and user speed to adapt HO margin(HM)and time to trigger(TTT).Estimated HM and TTT depend on a weighting function and HO type which is represented by user status during mobility.The proposed technique is validated with other existing algorithms from the literature.Simulation results demonstrate that the proposed technique outperforms existing algorithms overall performance metrics.The proposed technique reduces the overall average HO ping-pong probability,HO failure rate and interruption time by more than 90%,46%and 58%,respectively,compared with the other schemes overall speed scenarios and simulation time.
文摘In this paper we focus on the target capturing problem for a swarm of agents modelled as double integrators in any finite space dimension.Each agent knows the relative position of the target and has only an estimation of its velocity and acceleration.Given that the estimation errors are bounded by some known values,it is possible to design a control law that ensures that agents enter a user-defined ellipsoidal ring around the moving target.Agents know the relative position of the other members whose distance is smaller than a common detection radius.Finally,in the case of no uncertainty about target data and homogeneous agents,we show how the swarm can reach a static configuration around the moving target.Some simulations are reported to show the effectiveness of the proposed strategy.
基金The research leading to these results has received funding from The Research Council(TRC)of the Sultanate of Oman under the Block Funding Program with Agreement No.TRC/BFP/ASU/01/2019.
文摘Mobile broadband(MBB)networks are expanding rapidly to deliver higher data speeds.The fifth-generation cellular network promises enhanced-MBB with high-speed data rates,low power connectivity,and ultralow latency video streaming.However,existing cellular networks are unable to perform well due to high latency and low bandwidth,which degrades the performance of various applications.As a result,monitoring and evaluation of the performance of these network-supported services is critical.Mobile network providers optimize and monitor their network performance to ensure the highest quality of service to their end-users.This paper proposes a Bayesian model to estimate the minimum opinion score(MOS)of video streaming services for any particular cellular network.The MOS is the most commonly used metric to assess the quality of experience.The proposed Bayesian model consists of several input data,namely,round-trip time,stalling load,and bite rates.It was examined and evaluated using several test data sizes with various performance metrics.Simulation results show the proposed Bayesian network achieved higher accuracy overall test data sizes than a neural network.The proposed Bayesian network obtained a remarkable overall accuracy of 90.36%and outperformed the neural network.
基金This work was supported in part by the German Academic Exchange Service(Deutsche Akademische Austausch Dienst(DAAD)),and in part by the University of Kassel.
文摘Intracavity absorption spectroscopy is a strikingly sensitive technique that has been integrated with a two-wavelength setup to develop a sensor for human breath.Various factors are considered in such a scenario,out of which Relative Intensity Noise(RIN)has been exploited as an important parameter to characterize and calibrate the said setup.During the performance of an electrical based assessment arrangement which has been developed in the laboratory as an alternative to the expensive Agilent setup,the optical amplifier plays a pivotal role in its development and operation,along with other components and their significance.Therefore,the investigation and technical analysis of the amplifier in the system has been explored in detail.The algorithm developed for the automatic measurements of the system has been effectively deployed in terms of the laser’s performance.With this in perspective,a frequency dependent calibration has been pursued in depth with this scheme which enhances the sensor’s efficiency in terms of its sensitivity.In this way,our investigation helps us in a better understanding and implementation perspective of the proposed system,as the outcomes of our analysis adds to the precision and accuracy of the entire system.
文摘Necessity of electricity access in remote area is the main reason for expanding decentralized energy system such as stand-alone power systems. The best electrical power supply must provide a constant magnitude and frequency voltage. Therefore, good power quality is an important factor for the reliable operation of electrical loads in a power system. However, the current drawn by most of electronic devices and non-linear loads are non-sinusoidal, which can result in a poor power quality, especially in off-grid power systems. Poor power quality is characterized by electrical disturbances such as transients, sags, swells, harmonics and even interruptions in the power supply. Off-grid power systems worldwide often struggle with system failures and equipment damage due to poor power quality. In this paper, MAT- LAB/Simulink is used to model and analyses power quality in an off-grid renewable energy system. The results show high voltage transient when the inductive loads were switched OFF. The voltage and current harmonics are also determined and compared for various types of loads.
文摘Load Frequency Control (LFC) is one of power systems important requirements which maintain the zero steady-state errors in the frequency changing and restoring the natural frequency to its normal position. Many problems are subject to LFC such as suddenly large load or suddenly disconnecting generating unit by the protection device. In this paper, multi-area Frequency Control by using the combination of PSO and fuzzy logic control (FLC) technique. PSO optimization method is used to tuning the fuzzy controller input and output gains. Four of an interconnected electrical power system used as a testing the effectiveness of the proposed method compared to a conventional PI controller and scaled-fuzzy controller. The simulation result has been shown that the controller can generate the best dynamic response in multi-load conditions.
文摘The evaluation of distortion diagnosis using Wavelet function for Electrocardiogram (ECG), Electroencephalogram (EEG) and Phonocardiography (PCG) is not novel. However, some of the technological and economic issues remain challenging. The work in this paper is focusing on the reduction of the noise interferences and analyzes different kinds of ECG signals. Furthermore, a physiological monitoring system with a programming model for the filtration of ECG is presented. Kaiser based Finite Impulse Response (FIR) filter is used for noise reduction and identification of R peaks based on Peak Detection Algorithm (PDA). Two approaches are implemented for detecting the R peaks;Amplitude Threshold Value (ATV) and Peak Prediction Technique (PPT). Daubechies wavelet transform is applied to analyze the ECG of driver under stress, arrhythmia and sudden cardiac arrest signals. From the obtained results, it was found that the PPT is an effective and efficient technique in detecting the R peaks compared to ATV.
基金This research was supported by Ministry of Higher Education Malaysia(MOHE)through Fundamental Research Grant Scheme,FRGS/1/2017/TK04/UTHM/02/13Postgraduate Research Scheme,GPPS VOT H026.
文摘Sugar is important in daily food intake since it is used as food preservative and sweetener.Therefore,is important to analyze the influence of sugar on the spectroscopic properties of the sample.Terahertz spectroscopy is proven to be useful and an efficient method for sugar detection as well as for future food quality industry.However,the lack of detection sensitivity in Terahertz Spectroscopy has prevented it from being used in a widespread spectroscopic analysis technology.In this paper,Frequency Selective Surface(FSS)using the Terahertz Spectroscopy Time Domain Spectrum(THz-TDS)which operates at terahertz frequency range has been demonstrated for application of sugar detection.The FSS is designed with a circle slot structure and has been optimized in line with the molecular resonance of glucose and fructose at different level concentration at 1.98 THz and 1.80 THz,respectively.Transmission magnitude of glucose and sucrose is inversely proportional with the level of sugar concentrations.The realization of the FSS structure is using electron beam lithography and wet etching technique.Results show that the FSS performance for glucose and sucrose reveal fair shifts in measured transmission magnitude from its original in CST by approximately 30%.The use of fabricated FSS with circle structure indicates that the concentration can be improved averagely at 25%for glucose and 13%for sucrose.Thus,it shows that the FSS circle structure combined with THz-TDS has the potential to become an alternative method for food sensing technology in the future.
文摘Electrical transformers are vital components found virtually in most power-operated equipments. These transformers spontaneously radiate heat in both operation and steady-state mode. Should this thermal radiation inherent in transformers rises above allowable threshold a reduction in efficiency of operation occurs. In addition, this could cause other components in the system to malfunction. The aim of this work is to detect the remote causes of this undesirable thermal rise in transformers such as oil distribution transformers and ways to control this prevailing thermal problem. Oil transformers consist of these components: windings usually made of copper or aluminum conductor, the core normally made of silicon steel, the heat radiators, and the dielectric materials such as transformer oil, cellulose insulators and other peripherals. The Resistor-Inductor-Capacitor Thermal Network (RLCTN) model at architectural level identifies with these components to have ensemble operational mode as oil transformer. The Inductor represents the windings, the Resistor representing the core and the Capacitor represents the dielectrics. Thermography of transformer under various loading conditions was analyzed base on Infrared thermal gradient. Mathematical, experimental, and simulation results gotten through RLCTN with respect to time and thermal image analysis proved that the capacitance of the dielectric is inversely proportional to the thermal rise.
文摘<span style="white-space:normal;">This paper studies the influence factors of atoms number (N) at temperature (T) and after annealing time (t) on the structure shape and the plastic deformation of Polyethylene C</span><sub style="white-space:normal;">2</sub><span style="white-space:normal;">H</span><sub style="white-space:normal;">4</sub><span style="white-space:normal;"> (PE) by the Molecular Dynamics (MD) method with Dreading pair interaction, cyclic boundary conditions and plastic deformation of Polyethylene (PE) be done by stretching method according to the z-axis. The results of structure, plastic deformation of PE are analyzed through size (l), the total energy of the system (E</span><sub style="white-space:normal;">tot</sub><span style="white-space:normal;">), shape and associated energy (E</span><sub style="white-space:normal;">bond</sub><span style="white-space:normal;">), angular binding energy (E</span><sub style="white-space:normal;">angle</sub><span style="white-space:normal;">), energy E</span><sub style="white-space:normal;">dihedral</sub><span style="white-space:normal;">, interactive energy Vander Walls (E</span><sub style="white-space:normal;">non-bonding</sub><span style="white-space:normal;">). When increasing N, t leads to the number of structural units of Face-Centred Cubic (FCC), Body-Centered Cubic (BCC) and Hexagonal Close-Packed (HCP) increasing, but Amorphous (Amor) decreases while the angle between the atoms is a constant corresponding to 109.5</span>°<span style="white-space:normal;">. Besides, the length of the link (r) increases from r = 1.529 </span>Å<span style="white-space:normal;"> to r = 1.558 </span>Å<span style="white-space:normal;"> while the plastic deformation energy of PE gets an enormous change and the bonding angle at 109.27</span>°<span style="white-space:normal;">. The length of the link r = 1.529 </span>Å<span style="white-space:normal;"> and the size (l) of the PE material increase from l = 3.73 nm to l = 6.63 nm while the total energy of system (E</span><sub style="white-space:normal;">total</sub><span style="white-space:normal;">) decreases from E</span><sub style="white-space:normal;">total</sub><span style="white-space:normal;"> = <span style="white-space:nowrap;">−</span>1586 eV to E</span><sub style="white-space:normal;">total</sub><span style="white-space:normal;"> = <span style="white-space:nowrap;">−</span>7891 eV with the transition temperature is T = 103 K. Increasing the number of atoms leads to increasing the length of the link. The total energy E</span><sub style="white-space:normal;">total </sub><span style="white-space:normal;">of the system decreases, but the number of structural units in FCC, HCP, BCC and Amor increase, which leads to the length of the link increases, the E</span><sub style="white-space:normal;">total</sub><span style="white-space:normal;"> decreases, and there is a change in the plastic deformation characteristics of PE. In contrast, increasing T leads to the plastic deformation increases, and PE moves from the amorphous state to the liquid state. The obtained results are very significant for future experimental research.</span>
文摘Artificial intelligence,machine learning and deep learning algorithms have been widely used for Maximum Power Point Tracking(MPPT)in solar systems.In the traditional MPPT strategies,following of worldwide Global Maximum Power Point(GMPP)under incomplete concealing conditions stay overwhelming assignment and tracks different nearby greatest power focuses under halfway concealing conditions.The advent of artificial intelligence in MPPT has guaranteed of accurate following of GMPP while expanding the significant performance and efficiency of MPPT under Partial Shading Conditions(PSC).Still the selection of an efficient learning based MPPT is complex because each model has its advantages and drawbacks.Recently,Meta-heuristic algorithm based Learning techniques have provided better tracking efficiency but still exhibit dull performances under PSC.This work represents an excellent optimization based on Spotted Hyena Enabled Reliable BAT(SHERB)learning models,SHERB-MPPT integrated with powerful extreme learning machines to identify the GMPP with fast convergence,low steady-state oscillations,and good tracking efficiency.Extensive testing using MATLAB-SIMULINK,with 50000 data combinations gathered under partial shade and normal settings.As a result of simulations,the proposed approach offers 99.7%tracking efficiency with a slower convergence speed.To demonstrate the predominance of the proposed system,we have compared the performance of the system with other hybrid MPPT learning models.Results proved that the proposed cross breed MPPT model had beaten different techniques in recognizing GMPP viably under fractional concealing conditions.
文摘We propose a modified Fitzhugh-Nagumo neuron(MFNN) model. Based on this model, an integerorder MFNN system(case A) and a fractional-order MFNN system(case B) were investigated. In the presence of electromagnetic induction and radiation, memductance and induction can show a variety of distributions. Fractionalorder magnetic flux can then be considered. Indeed, a fractional-order setting can be acceptable for non-uniform diffusion. In the case of an MFNN system with integer-order discontinuous magnetic flux, the system has chaotic and non-chaotic attractors. Dynamical analysis of the system shows the birth and death of period doubling, which is a sign of antimonotonicity. Such a behavior has not been studied previously in the dynamics of neurons. In an MFNN system with fractional-order discontinuous magnetic flux, different attractors such as chaotic and periodic attractors can be observed. However, there is no sign of antimonotonicity.
