The gate assignment at an airport is one of the major activities in airport operations.With the increase of passenger traffic volumes and the number of flights, the complexity of this task and the factors to be consid...The gate assignment at an airport is one of the major activities in airport operations.With the increase of passenger traffic volumes and the number of flights, the complexity of this task and the factors to be considered have increased significantly, and an efficient gate utilizationhas received considerable attention. For overcoming the shortcomings of previous gate assignmentapproaches, this paper presents a partial parallel gate assignment approach, by which more factorsconcerning aircraft and gates can be collsidered at the same time. This paper also presents themethod of using a knowledge-based system combined with a mathematical programming method forgetting an optimized feasible assignment solution. By this way, it is more easily to get the solutionthat satisfies both the static and dynamic situations,and thus it may adapt well to meet the needsof actual use to rea-time operations. An experimental prototype has been implemented, and a casestudy is presented at the end of the paper.展开更多
Systems biology requires the development of algorithms that use omics data to infer interaction networks among biomolecules working within an organism. One major type of evolutionary algorithm, genetic programming (GP...Systems biology requires the development of algorithms that use omics data to infer interaction networks among biomolecules working within an organism. One major type of evolutionary algorithm, genetic programming (GP), is useful for its high heuristic ability as a search method for obtaining suitable solutions expressed as tree structures. However, because GP determines the values of parameters such as coefficients by random values, it is difficult to apply in the inference of state equations that describe oscillatory biochemical reaction systems with high nonlinearity. Accordingly, in this study, we propose a new GP procedure called “k-step GP” intended for inferring the state equations of oscillatory biochemical reaction systems. The k-step GP procedure consists of two algorithms: 1) Parameter optimization using the modified Powell method—after genetic operations such as crossover and mutation, the values of parameters such as coefficients are optimized by applying the modified Powell method with secondary convergence. 2) GP using divided learning data—to improve the inference efficiency, imposes perturbations through the addition of learning data at various intervals and adaptations to these changes result in state equations with higher fitness. We are confident that k-step GP is an algorithm that is particularly well suited to inferring state equations for oscillatory biochemical reaction systems and contributes to solving inverse problems in systems biology.展开更多
In this paper, at first, the single input rule modules(SIRMs) dynamically connected fuzzy inference model is used to stabilize a double inverted pendulum system. Then, a multiobjective particle swarm optimization(MOPS...In this paper, at first, the single input rule modules(SIRMs) dynamically connected fuzzy inference model is used to stabilize a double inverted pendulum system. Then, a multiobjective particle swarm optimization(MOPSO) is implemented to optimize the fuzzy controller parameters in order to decrease the distance error of the cart and summation of the angle errors of the pendulums, simultaneously. The feasibility and efficiency of the proposed Pareto front is assessed in comparison with results reported in literature and obtained from other algorithms.Finally, the Java programming with applets is utilized to simulate the stability of the nonlinear system and explain the internetbased control.展开更多
A neruon-oriented programming system based on parallel neural information processing has been presented. With the neural programming system built upon 4～8 process elements(TMS C30), the system has thus provided users...A neruon-oriented programming system based on parallel neural information processing has been presented. With the neural programming system built upon 4～8 process elements(TMS C30), the system has thus provided users high speed, general purpose and large scale neural network application development platforms etc.展开更多
Water-Decision Support System (DSS) tools enhance decision-makings towards improved water supply in a given region. The rigours of manual design of the conventional water treatment plants are easily eliminated with th...Water-Decision Support System (DSS) tools enhance decision-makings towards improved water supply in a given region. The rigours of manual design of the conventional water treatment plants are easily eliminated with the use of softwares as in the case of DSS. Therefore, this paper focuses on the development of a Water-DSS for design of treatment plant in Karkala Town, Udupi District of India. A four-decade population projection was made using the baseline data of 1971 till date. The manual computation for water demand, unit operations and adjoining facilities was carried out and later coded in C-programming language for development of a DSS for easier design and process selection. Data validation was done and results from the two approaches were compared. With the C-programming technique, a decision support tool for design and process selection of drinking water treatment plant using conventional method has been developed and named Water-DSS1. The designed tool is simple, accurate, flexible, efficient and universal, easily adaptable to any similar conventional treatment plant. Water-DSS1 is thus recommended for general use in ultimately alleviating water supply challenges.展开更多
When acquaintances of a model are little or the model is too complicate to build by using traditional time series methods, it is convenient for us to take advantage of genetic programming (GP) to build the model. Cons...When acquaintances of a model are little or the model is too complicate to build by using traditional time series methods, it is convenient for us to take advantage of genetic programming (GP) to build the model. Considering the complexity of nonlinear dynamic systems, this paper proposes modeling dynamic systems by using the nonlinear difference e-quation based on GP technique. First it gives the method, criteria and evaluation of modeling. Then it describes the modeling algorithm using GP. Finally two typical examples of time series are used to perform the numerical experiments. The result shows that this algorithm can successfully establish the difference equation model of dynamic systems and its predictive result is also satisfactory.展开更多
There is a growing technological development in intelligent teaching systems. This field has become interesting to many researchers. In this paper, we present an intelligent tutoring system for teaching mathematics th...There is a growing technological development in intelligent teaching systems. This field has become interesting to many researchers. In this paper, we present an intelligent tutoring system for teaching mathematics that helps students understand the basics of linear programming using Linear Program Solver and Service for Solving Linear Programming Problems, through which students will be able to solve economic problems. It comes down to determining the minimum or maximum value of a linear function, which is called the objective function, according to pre-set limiting conditions expressed by linear equations and inequalities. The goal function and the limiting conditions represent a mathematical model of the observed problem. Working as a professor of mathematics in high school, I felt the need for one such work and dealing with the study of linear programming as an integral part of mathematics. There are a number of papers in this regard, but exclusively related to traditional ways of working, as stated in the introductory part of the paper. The center of work as well as the final part deals with the study of linear programming using programs that deal with this topic.展开更多
This paper presents a new design approach to achieve decentralized optimal control of high-dimension complex singular systems with dynamic uncertainties. Based on robust adaptive dynamic programming(robust ADP) method...This paper presents a new design approach to achieve decentralized optimal control of high-dimension complex singular systems with dynamic uncertainties. Based on robust adaptive dynamic programming(robust ADP) method, controllers for solving the singular systems optimal control problem are designed. The proposed algorithm can work well when the system model is not exactly known but the input and output data can be measured. The policy iteration of each controller only uses their own states and input information for learning,and do not need to know the whole system dynamics. Simulation results on the New England 10-machine 39-bus test system show the effectiveness of the designed controller.展开更多
By the analysis of roller gear processing technology, combining with gear meshing mechanism and motion relationship, models for rolling gear machining parameter and zero-programming are established. In this paper, the...By the analysis of roller gear processing technology, combining with gear meshing mechanism and motion relationship, models for rolling gear machining parameter and zero-programming are established. In this paper, the automatic generation technology of NC program for CNC gear machining process has been studied and the zero-programming system architecture of open CNC gear-hobbing machine has been presented. In the design and development of the system, human computer interaction, programming algorithm and the design of each function module have bean done. Application test shows that the expected design requirements have been achieved.展开更多
Reliability optimization plays an important role in design, operation and management of the industrial systems. System reliability can be easily enhanced by improving the reliability of unreliable components and/or by...Reliability optimization plays an important role in design, operation and management of the industrial systems. System reliability can be easily enhanced by improving the reliability of unreliable components and/or by using redundant configuration with subsystems/components in parallel. Redundancy Allocation Problem (RAP) was studied in this research. A mixed integer programming model was proposed to solve the problem, which considers simultaneously two objectives under several resource constraints. The model is only for the hierarchical series-parallel systems in which the elements of any subset of subsystems or components are connected in series or parallel and constitute a larger subsystem or total system. At the end of the study, the performance of the proposed approach was evaluated by a numerical example.展开更多
Dynamic Programming (DP) algorithm is used to find the optimal trajectories under Beijing cycle for the power management of synergic electric system (SES) which is composed of battery and super capacitor. Feasible rul...Dynamic Programming (DP) algorithm is used to find the optimal trajectories under Beijing cycle for the power management of synergic electric system (SES) which is composed of battery and super capacitor. Feasible rules are derived from analyzing the optimal trajectories, and it has the highest contribution to Hybrid Electric Vehicle (HEV). The methods of how to get the best performance is also educed. Using the new Rule-based power management strat-egy adopted from the optimal results, it is easy to demonstrate the effectiveness of the new strategy in further improvement of the fuel economy by the synergic hybrid system.展开更多
文摘The gate assignment at an airport is one of the major activities in airport operations.With the increase of passenger traffic volumes and the number of flights, the complexity of this task and the factors to be considered have increased significantly, and an efficient gate utilizationhas received considerable attention. For overcoming the shortcomings of previous gate assignmentapproaches, this paper presents a partial parallel gate assignment approach, by which more factorsconcerning aircraft and gates can be collsidered at the same time. This paper also presents themethod of using a knowledge-based system combined with a mathematical programming method forgetting an optimized feasible assignment solution. By this way, it is more easily to get the solutionthat satisfies both the static and dynamic situations,and thus it may adapt well to meet the needsof actual use to rea-time operations. An experimental prototype has been implemented, and a casestudy is presented at the end of the paper.
文摘Systems biology requires the development of algorithms that use omics data to infer interaction networks among biomolecules working within an organism. One major type of evolutionary algorithm, genetic programming (GP), is useful for its high heuristic ability as a search method for obtaining suitable solutions expressed as tree structures. However, because GP determines the values of parameters such as coefficients by random values, it is difficult to apply in the inference of state equations that describe oscillatory biochemical reaction systems with high nonlinearity. Accordingly, in this study, we propose a new GP procedure called “k-step GP” intended for inferring the state equations of oscillatory biochemical reaction systems. The k-step GP procedure consists of two algorithms: 1) Parameter optimization using the modified Powell method—after genetic operations such as crossover and mutation, the values of parameters such as coefficients are optimized by applying the modified Powell method with secondary convergence. 2) GP using divided learning data—to improve the inference efficiency, imposes perturbations through the addition of learning data at various intervals and adaptations to these changes result in state equations with higher fitness. We are confident that k-step GP is an algorithm that is particularly well suited to inferring state equations for oscillatory biochemical reaction systems and contributes to solving inverse problems in systems biology.
基金supported by National Natural Science Foundation of China(61100159,61233007)National High Technology Research and Development Program of China(863 Program)(2011AA040103)+2 种基金Foundation of Chinese Academy of Sciences(KGCX2-EW-104)Financial Support of the Strategic Priority Research Program of Chinese Academy of Sciences(XDA06021100)the Cross-disciplinary Collaborative Teams Program for Science,Technology and Innovation,of Chinese Academy of Sciences-Network and System Technologies for Security Monitoring and Information Interaction in Smart Grid Energy Management System for Micro-smart Grid
文摘In this paper, at first, the single input rule modules(SIRMs) dynamically connected fuzzy inference model is used to stabilize a double inverted pendulum system. Then, a multiobjective particle swarm optimization(MOPSO) is implemented to optimize the fuzzy controller parameters in order to decrease the distance error of the cart and summation of the angle errors of the pendulums, simultaneously. The feasibility and efficiency of the proposed Pareto front is assessed in comparison with results reported in literature and obtained from other algorithms.Finally, the Java programming with applets is utilized to simulate the stability of the nonlinear system and explain the internetbased control.
文摘A neruon-oriented programming system based on parallel neural information processing has been presented. With the neural programming system built upon 4～8 process elements(TMS C30), the system has thus provided users high speed, general purpose and large scale neural network application development platforms etc.
文摘Water-Decision Support System (DSS) tools enhance decision-makings towards improved water supply in a given region. The rigours of manual design of the conventional water treatment plants are easily eliminated with the use of softwares as in the case of DSS. Therefore, this paper focuses on the development of a Water-DSS for design of treatment plant in Karkala Town, Udupi District of India. A four-decade population projection was made using the baseline data of 1971 till date. The manual computation for water demand, unit operations and adjoining facilities was carried out and later coded in C-programming language for development of a DSS for easier design and process selection. Data validation was done and results from the two approaches were compared. With the C-programming technique, a decision support tool for design and process selection of drinking water treatment plant using conventional method has been developed and named Water-DSS1. The designed tool is simple, accurate, flexible, efficient and universal, easily adaptable to any similar conventional treatment plant. Water-DSS1 is thus recommended for general use in ultimately alleviating water supply challenges.
基金Supported by Foundation for University Key Teacher by the Ministry of Education of China
文摘When acquaintances of a model are little or the model is too complicate to build by using traditional time series methods, it is convenient for us to take advantage of genetic programming (GP) to build the model. Considering the complexity of nonlinear dynamic systems, this paper proposes modeling dynamic systems by using the nonlinear difference e-quation based on GP technique. First it gives the method, criteria and evaluation of modeling. Then it describes the modeling algorithm using GP. Finally two typical examples of time series are used to perform the numerical experiments. The result shows that this algorithm can successfully establish the difference equation model of dynamic systems and its predictive result is also satisfactory.
文摘There is a growing technological development in intelligent teaching systems. This field has become interesting to many researchers. In this paper, we present an intelligent tutoring system for teaching mathematics that helps students understand the basics of linear programming using Linear Program Solver and Service for Solving Linear Programming Problems, through which students will be able to solve economic problems. It comes down to determining the minimum or maximum value of a linear function, which is called the objective function, according to pre-set limiting conditions expressed by linear equations and inequalities. The goal function and the limiting conditions represent a mathematical model of the observed problem. Working as a professor of mathematics in high school, I felt the need for one such work and dealing with the study of linear programming as an integral part of mathematics. There are a number of papers in this regard, but exclusively related to traditional ways of working, as stated in the introductory part of the paper. The center of work as well as the final part deals with the study of linear programming using programs that deal with this topic.
基金Supported by National High Technology Research and Development Program of China （863 Program） （2006AA04Z183）, National Nat- ural Science Foundation of China （60621001, 60534010, 60572070, 60774048, 60728307）, and the Program for Changjiang Scholars and Innovative Research Groups of China （60728307, 4031002）
基金supported in part by the National Natural Science Foundation of China(61473070,61433004,61627809)SAPI Fundamental Research Funds(2018ZCX22)
文摘This paper presents a new design approach to achieve decentralized optimal control of high-dimension complex singular systems with dynamic uncertainties. Based on robust adaptive dynamic programming(robust ADP) method, controllers for solving the singular systems optimal control problem are designed. The proposed algorithm can work well when the system model is not exactly known but the input and output data can be measured. The policy iteration of each controller only uses their own states and input information for learning,and do not need to know the whole system dynamics. Simulation results on the New England 10-machine 39-bus test system show the effectiveness of the designed controller.
基金supported by the Natural Science Foundation of Sichuan Province Education Department(16ZB0551)College enterprise cooperation research project(ybzysc14-10)
文摘By the analysis of roller gear processing technology, combining with gear meshing mechanism and motion relationship, models for rolling gear machining parameter and zero-programming are established. In this paper, the automatic generation technology of NC program for CNC gear machining process has been studied and the zero-programming system architecture of open CNC gear-hobbing machine has been presented. In the design and development of the system, human computer interaction, programming algorithm and the design of each function module have bean done. Application test shows that the expected design requirements have been achieved.
文摘Reliability optimization plays an important role in design, operation and management of the industrial systems. System reliability can be easily enhanced by improving the reliability of unreliable components and/or by using redundant configuration with subsystems/components in parallel. Redundancy Allocation Problem (RAP) was studied in this research. A mixed integer programming model was proposed to solve the problem, which considers simultaneously two objectives under several resource constraints. The model is only for the hierarchical series-parallel systems in which the elements of any subset of subsystems or components are connected in series or parallel and constitute a larger subsystem or total system. At the end of the study, the performance of the proposed approach was evaluated by a numerical example.
文摘Dynamic Programming (DP) algorithm is used to find the optimal trajectories under Beijing cycle for the power management of synergic electric system (SES) which is composed of battery and super capacitor. Feasible rules are derived from analyzing the optimal trajectories, and it has the highest contribution to Hybrid Electric Vehicle (HEV). The methods of how to get the best performance is also educed. Using the new Rule-based power management strat-egy adopted from the optimal results, it is easy to demonstrate the effectiveness of the new strategy in further improvement of the fuel economy by the synergic hybrid system.
