As the main link of ground engineering,crude oil gathering and transportation systems require huge energy consumption and complex structures.It is necessary to establish an energy efficiency evaluation system for crud...As the main link of ground engineering,crude oil gathering and transportation systems require huge energy consumption and complex structures.It is necessary to establish an energy efficiency evaluation system for crude oil gathering and transportation systems and identify the energy efficiency gaps.In this paper,the energy efficiency evaluation system of the crude oil gathering and transportation system in an oilfield in western China is established.Combined with the big data analysis method,the GA-BP neural network is used to establish the energy efficiency index prediction model for crude oil gathering and transportation systems.The comprehensive energy consumption,gas consumption,power consumption,energy utilization rate,heat utilization rate,and power utilization rate of crude oil gathering and transportation systems are predicted.Considering the efficiency and unit consumption index of the crude oil gathering and transportation system,the energy efficiency evaluation system of the crude oil gathering and transportation system is established based on a game theory combined weighting method and TOPSIS evaluation method,and the subjective weight is determined by the triangular fuzzy analytic hierarchy process.The entropy weight method determines the objective weight,and the combined weight of game theory combines subjectivity with objectivity to comprehensively evaluate the comprehensive energy efficiency of crude oil gathering and transportation systems and their subsystems.Finally,the weak links in energy utilization are identified,and energy conservation and consumption reduction are improved.The above research provides technical support for the green,efficient and intelligent development of crude oil gathering and transportation systems.展开更多
It is necessary to construct an effective trust model to build trust relationship between peers in peer-to-peer （P2P） network and enhance the security and reliability of P2P systems. The current trust models only fo...It is necessary to construct an effective trust model to build trust relationship between peers in peer-to-peer （P2P） network and enhance the security and reliability of P2P systems. The current trust models only focus on the consumers＇ evaluation to a transaction, which may be abused by malicious peers to exaggerate or slander the provider deliberately. In this paper, we propose a novel trust model based on mutual evaluation, called METrust, to suppress the peers＇ malicious behavior, such as dishonest evaluation and strategic attack. METrust considers the factors including mutual evaluation, similarity risk, time window, incentive, and punishment mechanism. The trust value is composed of the direct trust value and the recommendation trust value. In order to inhibit dishonest evaluation, both participants should give evaluation information based on peers＇ own experiences about the transaction while computing the direct trust value. In view of this, the mutual evaluation consistency factor and its time decay function are proposed. Besides, to reduce the risk of computing the recommendation trust based on the recommendations of friend peers, the similarity risk is introduced to measure the uncertainty of the similarity computing, while similarity is used to measure credibility. The experimental results show that METrust is effective, and it has advantages in the inhibition of the various malicious behaviors.展开更多
Introduction: In developing countries, gender-based violence (GBV) is a real public health problem. In Benin, GBV affects the majority of women and girls (69%). Benin has implemented strategies and set up integrated c...Introduction: In developing countries, gender-based violence (GBV) is a real public health problem. In Benin, GBV affects the majority of women and girls (69%). Benin has implemented strategies and set up integrated centers for the management of violence in order to reduce cases of violence and ensure the holistic management of victims. The objective of our study was to assess the functionality of the network of sexual and reproductive health rights (SRHR) in case of GBV in the commune of Kpomasse in 2022. Method: This descriptive and evaluative study was conducted from March 21 to April 11, 2022. The sampling method used was non-probabilistic. Reasoned choice and convenience were the techniques used for the different targets of the study. The functionality of the SRHR service network was assessed first by calculating scores at the structure, process and outcome levels, and then by analysis using the human rights-based approach. Results: Out of the 34 GBV victims identified, only one had received a full response and 54% of the victims had no knowledge of SRHR. The lack of knowledge about health care facilities was 41% for victims and 80% for non-victims in the community who participated in the study. In the case of gender-based violence, the community preferred to settle out of court rather than report it. The functionality of the networking of sexual and reproductive health rights services in the event of the occurrence of gender-based violence in the commune of Kpomassè is insufficient. Lack of knowledge of the roles of rights holders (DD) and duty bearers (DO) explains the insufficient functionality of networking. Conclusion: Training of SRHR service agents and community sensitization are essential to improve the functionality of SRHR service networking in the commune of Kpomasse.展开更多
On the basis of user satisfaction,authors made research hypotheses by learning from relevant e-service quality evaluation models.A questionnaire survey was then conducted on some content-based websites in terms of the...On the basis of user satisfaction,authors made research hypotheses by learning from relevant e-service quality evaluation models.A questionnaire survey was then conducted on some content-based websites in terms of their convenience,information quality,personalization and site aesthetics,which may affect the overall satisfaction of users.Statistical analysis was also made to build a user satisfaction-based quality evaluation system of network information service.展开更多
Accurate diagnosis of fracture geometry and conductivity is of great challenge due to the complex morphology of volumetric fracture network. In this study, a DNN (deep neural network) model was proposed to predict fra...Accurate diagnosis of fracture geometry and conductivity is of great challenge due to the complex morphology of volumetric fracture network. In this study, a DNN (deep neural network) model was proposed to predict fracture parameters for the evaluation of the fracturing effects. Field experience and the law of fracture volume conservation were incorporated as physical constraints to improve the prediction accuracy due to small amount of data. A combined neural network was adopted to input both static geological and dynamic fracturing data. The structure of the DNN was optimized and the model was validated through k-fold cross-validation. Results indicate that this DNN model is capable of predicting the fracture parameters accurately with a low relative error of under 10% and good generalization ability. The adoptions of the combined neural network, physical constraints, and k-fold cross-validation improve the model performance. Specifically, the root-mean-square error (RMSE) of the model decreases by 71.9% and 56% respectively with the combined neural network as the input model and the consideration of physical constraints. The mean square error (MRE) of fracture parameters reduces by 75% because the k-fold cross-validation improves the rationality of data set dividing. The model based on the DNN with physical constraints proposed in this study provides foundations for the optimization of fracturing design and improves the efficiency of fracture diagnosis in tight oil and gas reservoirs.展开更多
Research into automatically searching for an optimal neural network(NN)by optimi-sation algorithms is a significant research topic in deep learning and artificial intelligence.However,this is still challenging due to ...Research into automatically searching for an optimal neural network(NN)by optimi-sation algorithms is a significant research topic in deep learning and artificial intelligence.However,this is still challenging due to two issues:Both the hyperparameter and ar-chitecture should be optimised and the optimisation process is computationally expen-sive.To tackle these two issues,this paper focusses on solving the hyperparameter and architecture optimization problem for the NN and proposes a novel light‐weight scale‐adaptive fitness evaluation‐based particle swarm optimisation(SAFE‐PSO)approach.Firstly,the SAFE‐PSO algorithm considers the hyperparameters and architectures together in the optimisation problem and therefore can find their optimal combination for the globally best NN.Secondly,the computational cost can be reduced by using multi‐scale accuracy evaluation methods to evaluate candidates.Thirdly,a stagnation‐based switch strategy is proposed to adaptively switch different evaluation methods to better balance the search performance and computational cost.The SAFE‐PSO algorithm is tested on two widely used datasets:The 10‐category(i.e.,CIFAR10)and the 100−cate-gory(i.e.,CIFAR100).The experimental results show that SAFE‐PSO is very effective and efficient,which can not only find a promising NN automatically but also find a better NN than compared algorithms at the same computational cost.展开更多
With the rapid development of satellite technology, mega satellite constellations have become a research hotspot. A large number of related techniques have been developed on orbit topology, network routing, energy bal...With the rapid development of satellite technology, mega satellite constellations have become a research hotspot. A large number of related techniques have been developed on orbit topology, network routing, energy balance and resource control. However, it is difficult to accurately compare the performance of similar studies due to differences in the means of validation. Especially for invulnerability studies in many military applications, a unified evaluation system is essential. This paper proposes a network evaluation system for mega satellite constellations. Evaluation parameters include orbit topology, communication network, energy balance and invulnerability. Different application algorithms and traffic models were used to validate the specific system. .展开更多
The contribution rate of equipment system-of-systems architecture(ESoSA)is an important index to evaluate the equipment update,development,and architecture optimization.Since the traditional ESoSA contribution rate ev...The contribution rate of equipment system-of-systems architecture(ESoSA)is an important index to evaluate the equipment update,development,and architecture optimization.Since the traditional ESoSA contribution rate evaluation method does not make full use of the fuzzy information and uncertain information in the equipment system-of-systems(ESoS),and the Bayesian network is an effective tool to solve the uncertain information,a new ESoSA contribution rate evaluation method based on the fuzzy Bayesian network(FBN)is proposed.Firstly,based on the operation loop theory,an ESoSA is constructed considering three aspects:reconnaissance equipment,decision equipment,and strike equipment.Next,the fuzzy set theory is introduced to construct the FBN of ESoSA to deal with fuzzy information and uncertain information.Furthermore,the fuzzy importance index of the root node of the FBN is used to calculate the contribution rate of the ESoSA,and the ESoSA contribution rate evaluation model based on the root node fuzzy importance is established.Finally,the feasibility and rationality of this method are validated via an empirical case study of aviation ESoSA.Compared with traditional methods,the evaluation method based on FBN takes various failure states of equipment into consideration,is free of acquiring accurate probability of traditional equipment failure,and models the uncertainty of the relationship between equipment.The proposed method not only supplements and improves the ESoSA contribution rate assessment method,but also broadens the application scope of the Bayesian network.展开更多
Since the high penetration of renewable energy complicates the dynamic characteristics of the AC power electronic system(ACPES),it is essential to establish an accurate dynamic model to obtain its dynamic behavior for...Since the high penetration of renewable energy complicates the dynamic characteristics of the AC power electronic system(ACPES),it is essential to establish an accurate dynamic model to obtain its dynamic behavior for ensure the safe and stable operation of the system.However,due to the no or limited internal control details,the state-space modeling method cannot be realized.It leads to the ACPES system becoming a black-box dynamic system.The dynamic modeling method based on deep neural network can simulate the dynamic behavior using port data without obtaining internal control details.However,deep neural network modeling methods are rarely systematically evaluated.In practice,the construction of neural network faces the selection of massive data and various network structure parameters.However,different sample distributions make the trained network performance quite different.Different network structure hyperparameters also mean different convergence time.Due to the lack of systematic evaluation and targeted suggestions,neural network modeling with high precision and high training speed cannot be realized quickly and conveniently in practical engineering applications.To fill this gap,this paper systematically evaluates the deep neural network from sample distribution and structural hyperparameter selection.The influence on modeling accuracy is analyzed in detail,then some modeling suggestions are presented.Simulation results under multiple operating points verify the effectiveness of the proposed method.展开更多
A fuzzy neural network model is proposed to evaluate water quality. The model contains two parts： first, fuzzy mathematics theory is used to standardize the samples; second, the RBF neural network and the BP neural n...A fuzzy neural network model is proposed to evaluate water quality. The model contains two parts： first, fuzzy mathematics theory is used to standardize the samples; second, the RBF neural network and the BP neural network are used to train the standardized samples. The proposed model was applied to assess the water quality of 16 sections in 9 rivers in the Shaoguan area in 2005. The evaluation result was compared with that of the RBF neural network method and the reported results in the Shaoguan area in 2005. It indicated that the performance of the proposed fuzzy neural network model is practically feasible in the application of water quality assessment and its operation is simple.展开更多
This paper presents a web-based integrated system for on-line sensory fabric hand evaluation. The methods of fuzzy techniques, neural networks, classical factorial analysis and other data analysis are used in the syst...This paper presents a web-based integrated system for on-line sensory fabric hand evaluation. The methods of fuzzy techniques, neural networks, classical factorial analysis and other data analysis are used in the system to analyze the objective and subjective data, and to build the relationship between them. Given the objective data of a new fabric sample, the system can provide its sensory hand data and its total hand grade. In meantime, the total hand grade can be obtained directly from the sensory fabric hand data if provided. The sensory evaluation system is developed in Internet environment using Java language and SQL server database management system.展开更多
Aimed at the difficulties in accurately, comprehensively and systematically evaluating the reliability of industrial wireless sensor networks （WSNs）, a time-evolving state transition-Monte Carlo （TEST-MC） evaluati...Aimed at the difficulties in accurately, comprehensively and systematically evaluating the reliability of industrial wireless sensor networks （WSNs）, a time-evolving state transition-Monte Carlo （TEST-MC） evaluation method and a novel network function value representation method are proposed to evaluate the reliability of the IWSNs. First, the adjacency matrix method is used to characterize three typical topologies of WSNs including the mesh network, tree network and ribbon network. Secondly, the network function value method is used to evaluate the network connectivity, and the TEST-MC evaluation method is used to evaluate network reliability and availability. Finally, the variations in the reliability, connectivity and availability of these three topologies are presented. Simulation results show that the proposed method can quickly analyze the reliability of the networks containing typical WSN topologies, which provides an effective method for the comprehensive and accurate evaluation of the reliability of WSNs.展开更多
The back propagation (BP) model of artificial neural networks (ANN) has many good qualities comparing with ordinary methods in land suitability evaluation.Through analyzing ordinary methods’ limitations,some sticking...The back propagation (BP) model of artificial neural networks (ANN) has many good qualities comparing with ordinary methods in land suitability evaluation.Through analyzing ordinary methods’ limitations,some sticking points of BP model used in land evaluation,such as network structure,learning algorithm,etc.,are discussed in detail,The land evaluation of Qionghai city is used as a case study.Fuzzy comprehensive assessment method was also employed in this evaluation for validating and comparing.展开更多
Land evaluation factors often contain continuous-, discrete- and nominal-valued attributes. In traditional land evaluation, these different attributes are usually graded into categorical indexes by land resource exper...Land evaluation factors often contain continuous-, discrete- and nominal-valued attributes. In traditional land evaluation, these different attributes are usually graded into categorical indexes by land resource experts, and the evaluation results rely heavily on experts＇ experiences. In order to overcome the shortcoming, we presented a fuzzy neural network ensemble method that did not require grading the evaluation factors into categorical indexes and could evaluate land resources by using the three kinds of attribute values directly. A fuzzy back propagation neural network （BPNN）, a fuzzy radial basis function neural network （RBFNN）, a fuzzy BPNN ensemble, and a fuzzy RBFNN ensemble were used to evaluate the land resources in Guangdong Province. The evaluation results by using the fuzzy BPNN ensemble and the fuzzy RBFNN ensemble were much better than those by using the single fuzzy BPNN and the single fuzzy RBFNN, and the error rate of the single fuzzy RBFNN or fuzzy RBFNN ensemble was lower than that of the single fuzzy BPNN or fuzzy BPNN ensemble, respectively. By using the fuzzy neural network ensembles, the validity of land resource evaluation was improved and reliance on land evaluators＇ experiences was considerably reduced.展开更多
A self-organizing fuzzy clustering neural network by combining the self-organizing Kohonen clustering network with the fuzzy theory is proposed. This network model is designed for the effectiveness evaluation of elect...A self-organizing fuzzy clustering neural network by combining the self-organizing Kohonen clustering network with the fuzzy theory is proposed. This network model is designed for the effectiveness evaluation of electronic countermeasures, which not only exerts the advantages of the fuzzy theory, but also has a good ability in machine learning and data analysis. The subjective value of sample versus class is computed by the fuzzy computing theory, and the classified results obtained by self-organizing learning of Kohonen neural network are represented on output layer. Meanwhile, the fuzzy competition learning algorithm keeps the similar information between samples and overcomes the disadvantages of neural network which has fewer samples. The simulation result indicates that the proposed algorithm is feasible and effective.展开更多
Current design rationale （DR） systems have not demonstrated the value of the approach in practice since little attention is put to the evaluation method of DR knowledge. To systematize knowledge management process f...Current design rationale （DR） systems have not demonstrated the value of the approach in practice since little attention is put to the evaluation method of DR knowledge. To systematize knowledge management process for future computer-aided DR applications, a prerequisite is to provide the measure for the DR knowledge. In this paper, a new knowledge network evaluation method for DR management is presented. The method characterizes the DR knowledge value from four perspectives, namely, the design rationale structure scale, association knowledge and reasoning ability, degree of design justification support and degree of knowledge representation conciseness. The DR knowledge comprehensive value is also measured by the proposed method. To validate the proposed method, different style of DR knowledge network and the performance of the proposed measure are discussed. The evaluation method has been applied in two realistic design cases and compared with the structural measures. The research proposes the DR knowledge evaluation method which can provide object metric and selection basis for the DR knowledge reuse during the product design process. In addition, the method is proved to be more effective guidance and support for the application and management of DR knowledge.展开更多
Carrying out pilot project to provide broadband universal service nationwide, especially in rural impoverished areas, is a major policy decision in China. To accelerate implementation and ensure quality of the constru...Carrying out pilot project to provide broadband universal service nationwide, especially in rural impoverished areas, is a major policy decision in China. To accelerate implementation and ensure quality of the constructed network, it is of great significance to conduct comprehensive and scientific evaluation of the network status. In this paper, we present the evaluation of the broadband network constructed in rural China with several key indicators. It shows that with steppedup efforts of the telecom industry, broadband networks have been introduced into more and more villages. The average network speed reaches 60 Mbps, which is far exceeding 12 Mbps’ obligation.展开更多
In order to reduce the calculation of the failure probability in the complex mechanical system reliability risk evaluation,and to implement importance analysis of system components effectively,the system fault tree wa...In order to reduce the calculation of the failure probability in the complex mechanical system reliability risk evaluation,and to implement importance analysis of system components effectively,the system fault tree was converted into five different Bayesian network models. The Bayesian network with the minimum conditional probability table specification and the highest computation efficiency was selected as the optimal network. The two heuristics were used to optimize the Bayesian network. The fault diagnosis and causal reasoning of the system were implemented by using the selected Bayesian network. The calculation methods of Fussel-Vesely( FV),risk reduction worth( RRW),Birnbaum measure( BM) and risk achievement worth( RAW) importances were presented. A certain engine was taken as an application example to illustrate the proposed method. The results show that not only the correlation of the relevant variables in the system can be accurately expressed and the calculation complexity can be reduced,but also the relatively weak link in the system can be located accurately.展开更多
Simultaneous use of heterogeneous radio access technologies to increase the performance of real-time,reliability and capacity is an inherent feature of satellite-5G integrated network(Sat5G).However,there is still a l...Simultaneous use of heterogeneous radio access technologies to increase the performance of real-time,reliability and capacity is an inherent feature of satellite-5G integrated network(Sat5G).However,there is still a lack of theoretical characterization of whether the network can satisfy the end-to-end transmission performance for latency-sensitive service.To this end,we build a tandem model considering the connection relationship between the various components in Sat5G network architecture,and give an end-to-end latency calculation function based on this model.By introducing stochastic network calculus,we derive the relationship between the end-to-end latency bound and the violation probability considering the traffic characteristics of multimedia.Numerical results demonstrate the impact of different burst states and different service rates on this relationship,which means the higher the burst of arrival traffic and the higher the average rate of arrival traffic,the greater the probability of end-to-end latency violation.The results will provide valuable guidelines for the traffic control and cache management in Sat5G network.展开更多
A large number of spatial and attribute data are involved in coal resource evaluation. Database is a relatively advanced data management technology, but its Major defects are the poor graphic and spatial data function...A large number of spatial and attribute data are involved in coal resource evaluation. Database is a relatively advanced data management technology, but its Major defects are the poor graphic and spatial data functions, from which it is difficult to realize scientific management of evaluation data with spatial characteristics and evaluation result maps. On account of these deficiencies, the evaluation of degree of complexity of mining fault network, based on GIS, is proposed, which integrates management of spatial and attribute data. Fractal is an index which can reflect the comprehensive information of faults' number, density, size, composition and dynamics mechanism. Fractal dimension is used as the quantitative evaluation index. Evaluation software has been developed based on a component GIS-MapX, with which the degree of complexity of fault network is evaluated quantitatively using the quantitative index of fractal dimensions in Liuqiao No.2 coal mine as an example. Results show that it is effective in acquiring model parameters and enhancing the definition of data and evaluation results with the application of GIS technology. The fault network is a system with fractal structure and its complexity can be described reasonably and accurately by fractal dimension, which provides an effective method for coal resource evaluation.展开更多
基金This work was financially supported by the National Natural Science Foundation of China(52074089 and 52104064)Natural Science Foundation of Heilongjiang Province of China(LH2019E019).
文摘As the main link of ground engineering,crude oil gathering and transportation systems require huge energy consumption and complex structures.It is necessary to establish an energy efficiency evaluation system for crude oil gathering and transportation systems and identify the energy efficiency gaps.In this paper,the energy efficiency evaluation system of the crude oil gathering and transportation system in an oilfield in western China is established.Combined with the big data analysis method,the GA-BP neural network is used to establish the energy efficiency index prediction model for crude oil gathering and transportation systems.The comprehensive energy consumption,gas consumption,power consumption,energy utilization rate,heat utilization rate,and power utilization rate of crude oil gathering and transportation systems are predicted.Considering the efficiency and unit consumption index of the crude oil gathering and transportation system,the energy efficiency evaluation system of the crude oil gathering and transportation system is established based on a game theory combined weighting method and TOPSIS evaluation method,and the subjective weight is determined by the triangular fuzzy analytic hierarchy process.The entropy weight method determines the objective weight,and the combined weight of game theory combines subjectivity with objectivity to comprehensively evaluate the comprehensive energy efficiency of crude oil gathering and transportation systems and their subsystems.Finally,the weak links in energy utilization are identified,and energy conservation and consumption reduction are improved.The above research provides technical support for the green,efficient and intelligent development of crude oil gathering and transportation systems.
基金supported by National Natural Science Foundation of China (No.60873231)Research Fund for the Doctoral Program of Higher Education (No.20093223120001)+2 种基金Science and Technology Support Program of Jiangsu Province (No.BE2009158)Natural Science Fund of Higher Education of Jiangsu Province(No.09KJB520010)Special Fund for Fast Sharing of Science Paper in Net Era by CSTD (No.2009117)
文摘It is necessary to construct an effective trust model to build trust relationship between peers in peer-to-peer （P2P） network and enhance the security and reliability of P2P systems. The current trust models only focus on the consumers＇ evaluation to a transaction, which may be abused by malicious peers to exaggerate or slander the provider deliberately. In this paper, we propose a novel trust model based on mutual evaluation, called METrust, to suppress the peers＇ malicious behavior, such as dishonest evaluation and strategic attack. METrust considers the factors including mutual evaluation, similarity risk, time window, incentive, and punishment mechanism. The trust value is composed of the direct trust value and the recommendation trust value. In order to inhibit dishonest evaluation, both participants should give evaluation information based on peers＇ own experiences about the transaction while computing the direct trust value. In view of this, the mutual evaluation consistency factor and its time decay function are proposed. Besides, to reduce the risk of computing the recommendation trust based on the recommendations of friend peers, the similarity risk is introduced to measure the uncertainty of the similarity computing, while similarity is used to measure credibility. The experimental results show that METrust is effective, and it has advantages in the inhibition of the various malicious behaviors.
文摘Introduction: In developing countries, gender-based violence (GBV) is a real public health problem. In Benin, GBV affects the majority of women and girls (69%). Benin has implemented strategies and set up integrated centers for the management of violence in order to reduce cases of violence and ensure the holistic management of victims. The objective of our study was to assess the functionality of the network of sexual and reproductive health rights (SRHR) in case of GBV in the commune of Kpomasse in 2022. Method: This descriptive and evaluative study was conducted from March 21 to April 11, 2022. The sampling method used was non-probabilistic. Reasoned choice and convenience were the techniques used for the different targets of the study. The functionality of the SRHR service network was assessed first by calculating scores at the structure, process and outcome levels, and then by analysis using the human rights-based approach. Results: Out of the 34 GBV victims identified, only one had received a full response and 54% of the victims had no knowledge of SRHR. The lack of knowledge about health care facilities was 41% for victims and 80% for non-victims in the community who participated in the study. In the case of gender-based violence, the community preferred to settle out of court rather than report it. The functionality of the networking of sexual and reproductive health rights services in the event of the occurrence of gender-based violence in the commune of Kpomassè is insufficient. Lack of knowledge of the roles of rights holders (DD) and duty bearers (DO) explains the insufficient functionality of networking. Conclusion: Training of SRHR service agents and community sensitization are essential to improve the functionality of SRHR service networking in the commune of Kpomasse.
基金supported by the Ministry of Education of China(Grant No.06JJD870006)
文摘On the basis of user satisfaction,authors made research hypotheses by learning from relevant e-service quality evaluation models.A questionnaire survey was then conducted on some content-based websites in terms of their convenience,information quality,personalization and site aesthetics,which may affect the overall satisfaction of users.Statistical analysis was also made to build a user satisfaction-based quality evaluation system of network information service.
基金supported by the National Natural Science Foundation of China(Grant No.52174044,52004302)Science Foundation of China University of Petroleum,Beijing(No.ZX20200134,2462021YXZZ012)the Strategic Cooperation Technology Projects of CNPC and CUPB(ZLZX 2020-01-07).
文摘Accurate diagnosis of fracture geometry and conductivity is of great challenge due to the complex morphology of volumetric fracture network. In this study, a DNN (deep neural network) model was proposed to predict fracture parameters for the evaluation of the fracturing effects. Field experience and the law of fracture volume conservation were incorporated as physical constraints to improve the prediction accuracy due to small amount of data. A combined neural network was adopted to input both static geological and dynamic fracturing data. The structure of the DNN was optimized and the model was validated through k-fold cross-validation. Results indicate that this DNN model is capable of predicting the fracture parameters accurately with a low relative error of under 10% and good generalization ability. The adoptions of the combined neural network, physical constraints, and k-fold cross-validation improve the model performance. Specifically, the root-mean-square error (RMSE) of the model decreases by 71.9% and 56% respectively with the combined neural network as the input model and the consideration of physical constraints. The mean square error (MRE) of fracture parameters reduces by 75% because the k-fold cross-validation improves the rationality of data set dividing. The model based on the DNN with physical constraints proposed in this study provides foundations for the optimization of fracturing design and improves the efficiency of fracture diagnosis in tight oil and gas reservoirs.
基金supported in part by the National Key Research and Development Program of China under Grant 2019YFB2102102in part by the National Natural Science Foundations of China under Grant 62176094 and Grant 61873097+2 种基金in part by the Key‐Area Research and Development of Guangdong Province under Grant 2020B010166002in part by the Guangdong Natural Science Foundation Research Team under Grant 2018B030312003in part by the Guangdong‐Hong Kong Joint Innovation Platform under Grant 2018B050502006.
文摘Research into automatically searching for an optimal neural network(NN)by optimi-sation algorithms is a significant research topic in deep learning and artificial intelligence.However,this is still challenging due to two issues:Both the hyperparameter and ar-chitecture should be optimised and the optimisation process is computationally expen-sive.To tackle these two issues,this paper focusses on solving the hyperparameter and architecture optimization problem for the NN and proposes a novel light‐weight scale‐adaptive fitness evaluation‐based particle swarm optimisation(SAFE‐PSO)approach.Firstly,the SAFE‐PSO algorithm considers the hyperparameters and architectures together in the optimisation problem and therefore can find their optimal combination for the globally best NN.Secondly,the computational cost can be reduced by using multi‐scale accuracy evaluation methods to evaluate candidates.Thirdly,a stagnation‐based switch strategy is proposed to adaptively switch different evaluation methods to better balance the search performance and computational cost.The SAFE‐PSO algorithm is tested on two widely used datasets:The 10‐category(i.e.,CIFAR10)and the 100−cate-gory(i.e.,CIFAR100).The experimental results show that SAFE‐PSO is very effective and efficient,which can not only find a promising NN automatically but also find a better NN than compared algorithms at the same computational cost.
文摘With the rapid development of satellite technology, mega satellite constellations have become a research hotspot. A large number of related techniques have been developed on orbit topology, network routing, energy balance and resource control. However, it is difficult to accurately compare the performance of similar studies due to differences in the means of validation. Especially for invulnerability studies in many military applications, a unified evaluation system is essential. This paper proposes a network evaluation system for mega satellite constellations. Evaluation parameters include orbit topology, communication network, energy balance and invulnerability. Different application algorithms and traffic models were used to validate the specific system. .
基金supported by the National Key Research and Development Project(2018YFB1700802)the National Natural Science Foundation of China(72071206)the Science and Technology Innovation Plan of Hunan Province(2020RC4046).
文摘The contribution rate of equipment system-of-systems architecture(ESoSA)is an important index to evaluate the equipment update,development,and architecture optimization.Since the traditional ESoSA contribution rate evaluation method does not make full use of the fuzzy information and uncertain information in the equipment system-of-systems(ESoS),and the Bayesian network is an effective tool to solve the uncertain information,a new ESoSA contribution rate evaluation method based on the fuzzy Bayesian network(FBN)is proposed.Firstly,based on the operation loop theory,an ESoSA is constructed considering three aspects:reconnaissance equipment,decision equipment,and strike equipment.Next,the fuzzy set theory is introduced to construct the FBN of ESoSA to deal with fuzzy information and uncertain information.Furthermore,the fuzzy importance index of the root node of the FBN is used to calculate the contribution rate of the ESoSA,and the ESoSA contribution rate evaluation model based on the root node fuzzy importance is established.Finally,the feasibility and rationality of this method are validated via an empirical case study of aviation ESoSA.Compared with traditional methods,the evaluation method based on FBN takes various failure states of equipment into consideration,is free of acquiring accurate probability of traditional equipment failure,and models the uncertainty of the relationship between equipment.The proposed method not only supplements and improves the ESoSA contribution rate assessment method,but also broadens the application scope of the Bayesian network.
基金supported in part by the Science Search Foundation of Liaoning Educational Department。
文摘Since the high penetration of renewable energy complicates the dynamic characteristics of the AC power electronic system(ACPES),it is essential to establish an accurate dynamic model to obtain its dynamic behavior for ensure the safe and stable operation of the system.However,due to the no or limited internal control details,the state-space modeling method cannot be realized.It leads to the ACPES system becoming a black-box dynamic system.The dynamic modeling method based on deep neural network can simulate the dynamic behavior using port data without obtaining internal control details.However,deep neural network modeling methods are rarely systematically evaluated.In practice,the construction of neural network faces the selection of massive data and various network structure parameters.However,different sample distributions make the trained network performance quite different.Different network structure hyperparameters also mean different convergence time.Due to the lack of systematic evaluation and targeted suggestions,neural network modeling with high precision and high training speed cannot be realized quickly and conveniently in practical engineering applications.To fill this gap,this paper systematically evaluates the deep neural network from sample distribution and structural hyperparameter selection.The influence on modeling accuracy is analyzed in detail,then some modeling suggestions are presented.Simulation results under multiple operating points verify the effectiveness of the proposed method.
基金Supported by the National Key Research Program of China (No. 2003CCA00200)the Open Research Foundation of State KeyLab of Water Resources and Hydropower Engineering Science(No.2005C012).
文摘A fuzzy neural network model is proposed to evaluate water quality. The model contains two parts： first, fuzzy mathematics theory is used to standardize the samples; second, the RBF neural network and the BP neural network are used to train the standardized samples. The proposed model was applied to assess the water quality of 16 sections in 9 rivers in the Shaoguan area in 2005. The evaluation result was compared with that of the RBF neural network method and the reported results in the Shaoguan area in 2005. It indicated that the performance of the proposed fuzzy neural network model is practically feasible in the application of water quality assessment and its operation is simple.
基金supported by the joint Sino-French Advanced Research Program(No:PRA-SI-01-05)the National Natural Science Foundation(60004006)from P.R.China.
文摘This paper presents a web-based integrated system for on-line sensory fabric hand evaluation. The methods of fuzzy techniques, neural networks, classical factorial analysis and other data analysis are used in the system to analyze the objective and subjective data, and to build the relationship between them. Given the objective data of a new fabric sample, the system can provide its sensory hand data and its total hand grade. In meantime, the total hand grade can be obtained directly from the sensory fabric hand data if provided. The sensory evaluation system is developed in Internet environment using Java language and SQL server database management system.
基金The International S&T Cooperation Program of China(No.2015DFA10490)the National Natural Science Foundation of China(No.61571113,61240032)the Specialized Research Fund for the Doctoral Program of Higher Education(No.20130092110060)
文摘Aimed at the difficulties in accurately, comprehensively and systematically evaluating the reliability of industrial wireless sensor networks （WSNs）, a time-evolving state transition-Monte Carlo （TEST-MC） evaluation method and a novel network function value representation method are proposed to evaluate the reliability of the IWSNs. First, the adjacency matrix method is used to characterize three typical topologies of WSNs including the mesh network, tree network and ribbon network. Secondly, the network function value method is used to evaluate the network connectivity, and the TEST-MC evaluation method is used to evaluate network reliability and availability. Finally, the variations in the reliability, connectivity and availability of these three topologies are presented. Simulation results show that the proposed method can quickly analyze the reliability of the networks containing typical WSN topologies, which provides an effective method for the comprehensive and accurate evaluation of the reliability of WSNs.
文摘The back propagation (BP) model of artificial neural networks (ANN) has many good qualities comparing with ordinary methods in land suitability evaluation.Through analyzing ordinary methods’ limitations,some sticking points of BP model used in land evaluation,such as network structure,learning algorithm,etc.,are discussed in detail,The land evaluation of Qionghai city is used as a case study.Fuzzy comprehensive assessment method was also employed in this evaluation for validating and comparing.
基金the National Natural Science Foundation of China (No.40671145)the Natural Science Foundation of Guangdong Province (Nos.04300504 and 05006623)and the Science and Technology Plan Foundation of Guangdong Province (Nos.2005B20701008,2005B10101028,and 2004B20701006).
文摘Land evaluation factors often contain continuous-, discrete- and nominal-valued attributes. In traditional land evaluation, these different attributes are usually graded into categorical indexes by land resource experts, and the evaluation results rely heavily on experts＇ experiences. In order to overcome the shortcoming, we presented a fuzzy neural network ensemble method that did not require grading the evaluation factors into categorical indexes and could evaluate land resources by using the three kinds of attribute values directly. A fuzzy back propagation neural network （BPNN）, a fuzzy radial basis function neural network （RBFNN）, a fuzzy BPNN ensemble, and a fuzzy RBFNN ensemble were used to evaluate the land resources in Guangdong Province. The evaluation results by using the fuzzy BPNN ensemble and the fuzzy RBFNN ensemble were much better than those by using the single fuzzy BPNN and the single fuzzy RBFNN, and the error rate of the single fuzzy RBFNN or fuzzy RBFNN ensemble was lower than that of the single fuzzy BPNN or fuzzy BPNN ensemble, respectively. By using the fuzzy neural network ensembles, the validity of land resource evaluation was improved and reliance on land evaluators＇ experiences was considerably reduced.
文摘A self-organizing fuzzy clustering neural network by combining the self-organizing Kohonen clustering network with the fuzzy theory is proposed. This network model is designed for the effectiveness evaluation of electronic countermeasures, which not only exerts the advantages of the fuzzy theory, but also has a good ability in machine learning and data analysis. The subjective value of sample versus class is computed by the fuzzy computing theory, and the classified results obtained by self-organizing learning of Kohonen neural network are represented on output layer. Meanwhile, the fuzzy competition learning algorithm keeps the similar information between samples and overcomes the disadvantages of neural network which has fewer samples. The simulation result indicates that the proposed algorithm is feasible and effective.
基金Supported by National Natural Science Foundation of China(Grant Nos.51175019,61104169,51205321)
文摘Current design rationale （DR） systems have not demonstrated the value of the approach in practice since little attention is put to the evaluation method of DR knowledge. To systematize knowledge management process for future computer-aided DR applications, a prerequisite is to provide the measure for the DR knowledge. In this paper, a new knowledge network evaluation method for DR management is presented. The method characterizes the DR knowledge value from four perspectives, namely, the design rationale structure scale, association knowledge and reasoning ability, degree of design justification support and degree of knowledge representation conciseness. The DR knowledge comprehensive value is also measured by the proposed method. To validate the proposed method, different style of DR knowledge network and the performance of the proposed measure are discussed. The evaluation method has been applied in two realistic design cases and compared with the structural measures. The research proposes the DR knowledge evaluation method which can provide object metric and selection basis for the DR knowledge reuse during the product design process. In addition, the method is proved to be more effective guidance and support for the application and management of DR knowledge.
文摘Carrying out pilot project to provide broadband universal service nationwide, especially in rural impoverished areas, is a major policy decision in China. To accelerate implementation and ensure quality of the constructed network, it is of great significance to conduct comprehensive and scientific evaluation of the network status. In this paper, we present the evaluation of the broadband network constructed in rural China with several key indicators. It shows that with steppedup efforts of the telecom industry, broadband networks have been introduced into more and more villages. The average network speed reaches 60 Mbps, which is far exceeding 12 Mbps’ obligation.
基金National Natural Science Foundations of China(Nos.61164009,61463021)the Science Foundation of Education Commission of Jiangxi Province,China(No.GJJ14420)+1 种基金the Young Scientists Object Program of Jiangxi Province,China(No.20144BCB23037)the Graduate Innovation Foundation of Jiangxi Province,China(No.YC2014-S364)
文摘In order to reduce the calculation of the failure probability in the complex mechanical system reliability risk evaluation,and to implement importance analysis of system components effectively,the system fault tree was converted into five different Bayesian network models. The Bayesian network with the minimum conditional probability table specification and the highest computation efficiency was selected as the optimal network. The two heuristics were used to optimize the Bayesian network. The fault diagnosis and causal reasoning of the system were implemented by using the selected Bayesian network. The calculation methods of Fussel-Vesely( FV),risk reduction worth( RRW),Birnbaum measure( BM) and risk achievement worth( RAW) importances were presented. A certain engine was taken as an application example to illustrate the proposed method. The results show that not only the correlation of the relevant variables in the system can be accurately expressed and the calculation complexity can be reduced,but also the relatively weak link in the system can be located accurately.
基金This work was supported by the National Natural Science Foundation of China under Grants 61801073,61722105,61931004the Natural Science Foundation of Liaoning Province under Grant 20170540034.
文摘Simultaneous use of heterogeneous radio access technologies to increase the performance of real-time,reliability and capacity is an inherent feature of satellite-5G integrated network(Sat5G).However,there is still a lack of theoretical characterization of whether the network can satisfy the end-to-end transmission performance for latency-sensitive service.To this end,we build a tandem model considering the connection relationship between the various components in Sat5G network architecture,and give an end-to-end latency calculation function based on this model.By introducing stochastic network calculus,we derive the relationship between the end-to-end latency bound and the violation probability considering the traffic characteristics of multimedia.Numerical results demonstrate the impact of different burst states and different service rates on this relationship,which means the higher the burst of arrival traffic and the higher the average rate of arrival traffic,the greater the probability of end-to-end latency violation.The results will provide valuable guidelines for the traffic control and cache management in Sat5G network.
基金Project 50534050 supported by the National Natural Science Foundation of China
文摘A large number of spatial and attribute data are involved in coal resource evaluation. Database is a relatively advanced data management technology, but its Major defects are the poor graphic and spatial data functions, from which it is difficult to realize scientific management of evaluation data with spatial characteristics and evaluation result maps. On account of these deficiencies, the evaluation of degree of complexity of mining fault network, based on GIS, is proposed, which integrates management of spatial and attribute data. Fractal is an index which can reflect the comprehensive information of faults' number, density, size, composition and dynamics mechanism. Fractal dimension is used as the quantitative evaluation index. Evaluation software has been developed based on a component GIS-MapX, with which the degree of complexity of fault network is evaluated quantitatively using the quantitative index of fractal dimensions in Liuqiao No.2 coal mine as an example. Results show that it is effective in acquiring model parameters and enhancing the definition of data and evaluation results with the application of GIS technology. The fault network is a system with fractal structure and its complexity can be described reasonably and accurately by fractal dimension, which provides an effective method for coal resource evaluation.
