The simulation-based decision support system (SBDSS) is designed to achieve a highlevel of performance, flexibility and adaptability, in response to meet the special needs of productionand logistics management during ...The simulation-based decision support system (SBDSS) is designed to achieve a highlevel of performance, flexibility and adaptability, in response to meet the special needs of productionand logistics management during the economic system reform era in China. It consists two subsys-tems: the object library modeler (OLM) and the simulation engine and its manager (SEM). UsingSBDSS the decision makers can work out their optimal production choice under certain circumstancesthrough scenario simulations. And they can test a set of virtual organizations reflecting systems re-form before a real reorganization has been taken, as well as perform a virtual manufacturing processfor a new product design (Copyright @ 1998 IFAC).展开更多
Input-output data fitting methods are often used for unknown-structure nonlinear system modeling. Based on model-on-demand tactics, a multiple model approach to modeling for nonlinear systems is presented. The basic i...Input-output data fitting methods are often used for unknown-structure nonlinear system modeling. Based on model-on-demand tactics, a multiple model approach to modeling for nonlinear systems is presented. The basic idea is to find out, from vast historical system input-output data sets, some data sets matching with the current working point, then to develop a local model using Local Polynomial Fitting (LPF) algorithm. With the change of working points, multiple local models are built, which realize the exact modeling for the global system. By comparing to other methods, the simulation results show good performance for its simple, effective and reliable estimation.展开更多
In this paper, the stability analysis for parallel real-time digital simulation models is discussed. The coupling coefficient perturbation method and the simulation stepsize perturbation method are established. For tw...In this paper, the stability analysis for parallel real-time digital simulation models is discussed. The coupling coefficient perturbation method and the simulation stepsize perturbation method are established. For two classes of systems of test equations, we construct the parallel simulation models and prove that they have the stability behaviour which is similar to the original continuous systems.展开更多
This paper reports an aspiration-directed, model-based decision support system (AMDSS) integrated with a knowledge-based simulation system. The system is designed to study China's mid-range economic development st...This paper reports an aspiration-directed, model-based decision support system (AMDSS) integrated with a knowledge-based simulation system. The system is designed to study China's mid-range economic development strategy. The capacity of the system is enhanced by the knowledge-based component which provides a knowledge-based simulation environment for model management. Currently the system has passed the stage of prototype and achieves its implementation capacity. The paper first presents the mathematical aspects of decision making including aspiration-directed decision making, then discusses the architecture of the system. The purpose of the paper is to provide insights into how such an integrated system could provide decision support for complex decision analysis.展开更多
First of all, this paper discusses the drawbacks of multilayer perceptron (MLP), which is trained by the traditional back propagation (BP) algorithm and used in a special classification problem. A new training algorit...First of all, this paper discusses the drawbacks of multilayer perceptron (MLP), which is trained by the traditional back propagation (BP) algorithm and used in a special classification problem. A new training algorithm for neural networks based on genetic algorithm and BP algorithm is developed. The difference between the new training algorithm and BP algorithm in the ability of nonlinear approaching is expressed through an example, and the application foreground is illustrated by an example.展开更多
Milling Process Simulation is one of the important re search areas in manufacturing science. For the purpose of improving the prec ision of simulation and extending its usability, numerical algorithm is more and more ...Milling Process Simulation is one of the important re search areas in manufacturing science. For the purpose of improving the prec ision of simulation and extending its usability, numerical algorithm is more and more used in the milling modeling areas. But simulative efficiency is decreasin g with increase of its complexity. As a result, application of the method is lim ited. Aimed at above question, high-efficient algorithm for milling process sim ulation is studied. It is important for milling process simulation’s applicatio n. Parallel computing is widely used to solve the large-scale computation question s. Its advantages include system flexibility, robust, high-efficient computing capability and high ratio of performance to price. With the development of compu ter network, utilizing the computing resource in the Internet, a virtual computi ng environment with powerful computing capability can be consisted by microc omputers, and the difficulty of building hardware environment which is used to s upport parallel computing is reduced. How to use network technology and parallel algorithm to improve simulative effic iency for milling forces simulation is investigated in the paper. In order to pr edict milling forces, a simplified local milling forces model is used in the pap er. End milling cutter is assumed to be divided by r number of differential elem ents along the axial direction of the cutter. For a given time, the total cuttin g forces can be obtained by summarizing the resultant cutting force produced by each differential cutter disc. Divide the whole simulative time into some segmen ts, send these program’s segments to microcomputers in the Internet and obtain the result of the program’s segments, all of the result of program’s segments a re composed the final result. For implementing the algorithm, a distributed Parallel computing framework is de signed in the paper. In the framework, web server plays a role of controller. Us ing Java RMI(remote method interface), the computing processes in computing serv er are called by web server. There are lots of control processes in web server a nd control the computing servers. The codes of simulative algorithm can be dynam ic sent to the computing servers, and milling forces at the different time are c omputed through utilizing the local computer’s resource. The results that are ca lculated by every computing servers are sent to the web server, and composed the final result. The framework can be used by different simulative algorithm. Comp ared with the algorithm running single machine, the efficiency of provided algor ithm is higher than that of single machine.展开更多
The test selection and optimization （TSO） can improve the abilities of fault diagnosis, prognosis and health-state evalua- tion for prognostics and health management （PHM） systems. Traditionally, TSO mainly focuse...The test selection and optimization （TSO） can improve the abilities of fault diagnosis, prognosis and health-state evalua- tion for prognostics and health management （PHM） systems. Traditionally, TSO mainly focuses on fault detection and isolation, but they cannot provide an effective guide for the design for testability （DFT） to improve the PHM performance level. To solve the problem, a model of TSO for PHM systems is proposed. Firstly, through integrating the characteristics of fault severity and propa- gation time, and analyzing the test timing and sensitivity, a testability model based on failure evolution mechanism model （FEMM） for PHM systems is built up. This model describes the fault evolution- test dependency using the fault-symptom parameter matrix and symptom parameter-test matrix. Secondly, a novel method of in- herent testability analysis for PHM systems is developed based on the above information. Having completed the analysis, a TSO model, whose objective is to maximize fault trackability and mini- mize the test cost, is proposed through inherent testability analysis results, and an adaptive simulated annealing genetic algorithm （ASAGA） is introduced to solve the TSO problem. Finally, a case of a centrifugal pump system is used to verify the feasibility and effectiveness of the proposed models and methods. The results show that the proposed technology is important for PHM systems to select and optimize the test set in order to improve their performance level.展开更多
To improve the productivity of cluster tools in semiconductor fabrications,on the basis of stating scheduling problems,a try and error-based scheduling algorithm was proposed with residency time constraints and an obj...To improve the productivity of cluster tools in semiconductor fabrications,on the basis of stating scheduling problems,a try and error-based scheduling algorithm was proposed with residency time constraints and an objective of minimizing Makespan for the wafer jobs in cluster tools.Firstly,mathematical formulations of scheduling problems were presented by using assumptions and definitions of a scheduling domain.Resource conflicts were analyzed in the built scheduling model,and policies to solve resource conflicts were built.A scheduling algorithm was developed.Finally,the performances of the proposed algorithm were evaluated and compared with those of other methods by simulations.Experiment results indicate that the proposed algorithm is effective and practical in solving the scheduling problem of the cluster tools.展开更多
A hybrid feature selection and classification strategy was proposed based on the simulated annealing genetic algonthrn and multiple instance learning （MIL）. The band selection method was proposed from subspace decom...A hybrid feature selection and classification strategy was proposed based on the simulated annealing genetic algonthrn and multiple instance learning （MIL）. The band selection method was proposed from subspace decomposition, which combines the simulated annealing algorithm with the genetic algorithm in choosing different cross-over and mutation probabilities, as well as mutation individuals. Then MIL was combined with image segmentation, clustering and support vector machine algorithms to classify hyperspectral image. The experimental results show that this proposed method can get high classification accuracy of 93.13% at small training samples and the weaknesses of the conventional methods are overcome.展开更多
Accurate forecasting of wind velocity can improve the economic dispatch and safe operation of the power system. Support vector machine (SVM) has been proved to be an efficient approach for forecasting. According to th...Accurate forecasting of wind velocity can improve the economic dispatch and safe operation of the power system. Support vector machine (SVM) has been proved to be an efficient approach for forecasting. According to the analysis with support vector machine method, the drawback of determining the parameters only by experts' experience should be improved. After a detailed description of the methodology of SVM and simulated annealing, an improved algorithm was proposed for the automatic optimization of parameters using SVM method. An example has proved that the proposed method can efficiently select the parameters of the SVM method. And by optimizing the parameters, the forecasting accuracy of the max wind velocity increases by 34.45%, which indicates that the new SASVM model improves the forecasting accuracy.展开更多
According to time-sharing valuation principle (TSVP) of power supply, the relationships of current density and current efficiency at different acidities are obtained based on the processed data of electrolytic deposit...According to time-sharing valuation principle (TSVP) of power supply, the relationships of current density and current efficiency at different acidities are obtained based on the processed data of electrolytic deposition process of zinc (EDPZ) with the least square method (LSM). Thus an optimal model of time-sharing power supply system for EDPZ is established, which has been optimized by use of an improved efficient simulated annealing algorithm (SAA). Practical results show that industrial and mining enterprises can obtain enormous economic benefits every year.展开更多
The accuracy of present flatness predictive method is limited and it just belongs to software simulation. In order to improve it, a novel flatness predictive model via T-S cloud reasoning network implemented by digita...The accuracy of present flatness predictive method is limited and it just belongs to software simulation. In order to improve it, a novel flatness predictive model via T-S cloud reasoning network implemented by digital signal processor(DSP) is proposed. First, the combination of genetic algorithm(GA) and simulated annealing algorithm(SAA) is put forward, called GA-SA algorithm, which can make full use of the global search ability of GA and local search ability of SA. Later, based on T-S cloud reasoning neural network, flatness predictive model is designed in DSP. And it is applied to 900 HC reversible cold rolling mill. Experimental results demonstrate that the flatness predictive model via T-S cloud reasoning network can run on the hardware DSP TMS320 F2812 with high accuracy and robustness by using GA-SA algorithm to optimize the model parameter.展开更多
A nonlinear visual mapping model is presented to replace the image Jacobian relation for uncalibrated hand/eye coordination. A new visual tracking controller based on artificial neural network is designed. Simulation ...A nonlinear visual mapping model is presented to replace the image Jacobian relation for uncalibrated hand/eye coordination. A new visual tracking controller based on artificial neural network is designed. Simulation results show that this method can drive the static tracking error to zero quickly and keep good robustness and adaptability at the same time. In addition, the algorithm is very easy to be implemented with low computational complexity.展开更多
文摘The simulation-based decision support system (SBDSS) is designed to achieve a highlevel of performance, flexibility and adaptability, in response to meet the special needs of productionand logistics management during the economic system reform era in China. It consists two subsys-tems: the object library modeler (OLM) and the simulation engine and its manager (SEM). UsingSBDSS the decision makers can work out their optimal production choice under certain circumstancesthrough scenario simulations. And they can test a set of virtual organizations reflecting systems re-form before a real reorganization has been taken, as well as perform a virtual manufacturing processfor a new product design (Copyright @ 1998 IFAC).
基金This project was supported by National Natural Science Foundation (No. 69934020).
文摘Input-output data fitting methods are often used for unknown-structure nonlinear system modeling. Based on model-on-demand tactics, a multiple model approach to modeling for nonlinear systems is presented. The basic idea is to find out, from vast historical system input-output data sets, some data sets matching with the current working point, then to develop a local model using Local Polynomial Fitting (LPF) algorithm. With the change of working points, multiple local models are built, which realize the exact modeling for the global system. By comparing to other methods, the simulation results show good performance for its simple, effective and reliable estimation.
基金This work is supported partly by the National Natural Science Foundation of China
文摘In this paper, the stability analysis for parallel real-time digital simulation models is discussed. The coupling coefficient perturbation method and the simulation stepsize perturbation method are established. For two classes of systems of test equations, we construct the parallel simulation models and prove that they have the stability behaviour which is similar to the original continuous systems.
文摘This paper reports an aspiration-directed, model-based decision support system (AMDSS) integrated with a knowledge-based simulation system. The system is designed to study China's mid-range economic development strategy. The capacity of the system is enhanced by the knowledge-based component which provides a knowledge-based simulation environment for model management. Currently the system has passed the stage of prototype and achieves its implementation capacity. The paper first presents the mathematical aspects of decision making including aspiration-directed decision making, then discusses the architecture of the system. The purpose of the paper is to provide insights into how such an integrated system could provide decision support for complex decision analysis.
基金This project was supported by Guangdong Natural Science Foundation.
文摘First of all, this paper discusses the drawbacks of multilayer perceptron (MLP), which is trained by the traditional back propagation (BP) algorithm and used in a special classification problem. A new training algorithm for neural networks based on genetic algorithm and BP algorithm is developed. The difference between the new training algorithm and BP algorithm in the ability of nonlinear approaching is expressed through an example, and the application foreground is illustrated by an example.
文摘Milling Process Simulation is one of the important re search areas in manufacturing science. For the purpose of improving the prec ision of simulation and extending its usability, numerical algorithm is more and more used in the milling modeling areas. But simulative efficiency is decreasin g with increase of its complexity. As a result, application of the method is lim ited. Aimed at above question, high-efficient algorithm for milling process sim ulation is studied. It is important for milling process simulation’s applicatio n. Parallel computing is widely used to solve the large-scale computation question s. Its advantages include system flexibility, robust, high-efficient computing capability and high ratio of performance to price. With the development of compu ter network, utilizing the computing resource in the Internet, a virtual computi ng environment with powerful computing capability can be consisted by microc omputers, and the difficulty of building hardware environment which is used to s upport parallel computing is reduced. How to use network technology and parallel algorithm to improve simulative effic iency for milling forces simulation is investigated in the paper. In order to pr edict milling forces, a simplified local milling forces model is used in the pap er. End milling cutter is assumed to be divided by r number of differential elem ents along the axial direction of the cutter. For a given time, the total cuttin g forces can be obtained by summarizing the resultant cutting force produced by each differential cutter disc. Divide the whole simulative time into some segmen ts, send these program’s segments to microcomputers in the Internet and obtain the result of the program’s segments, all of the result of program’s segments a re composed the final result. For implementing the algorithm, a distributed Parallel computing framework is de signed in the paper. In the framework, web server plays a role of controller. Us ing Java RMI(remote method interface), the computing processes in computing serv er are called by web server. There are lots of control processes in web server a nd control the computing servers. The codes of simulative algorithm can be dynam ic sent to the computing servers, and milling forces at the different time are c omputed through utilizing the local computer’s resource. The results that are ca lculated by every computing servers are sent to the web server, and composed the final result. The framework can be used by different simulative algorithm. Comp ared with the algorithm running single machine, the efficiency of provided algor ithm is higher than that of single machine.
基金supported by the National Natural Science Foundation of China(51175502)
文摘The test selection and optimization （TSO） can improve the abilities of fault diagnosis, prognosis and health-state evalua- tion for prognostics and health management （PHM） systems. Traditionally, TSO mainly focuses on fault detection and isolation, but they cannot provide an effective guide for the design for testability （DFT） to improve the PHM performance level. To solve the problem, a model of TSO for PHM systems is proposed. Firstly, through integrating the characteristics of fault severity and propa- gation time, and analyzing the test timing and sensitivity, a testability model based on failure evolution mechanism model （FEMM） for PHM systems is built up. This model describes the fault evolution- test dependency using the fault-symptom parameter matrix and symptom parameter-test matrix. Secondly, a novel method of in- herent testability analysis for PHM systems is developed based on the above information. Having completed the analysis, a TSO model, whose objective is to maximize fault trackability and mini- mize the test cost, is proposed through inherent testability analysis results, and an adaptive simulated annealing genetic algorithm （ASAGA） is introduced to solve the TSO problem. Finally, a case of a centrifugal pump system is used to verify the feasibility and effectiveness of the proposed models and methods. The results show that the proposed technology is important for PHM systems to select and optimize the test set in order to improve their performance level.
基金Projects(71071115,60574054) supported by the National Natural Science Foundation of China
文摘To improve the productivity of cluster tools in semiconductor fabrications,on the basis of stating scheduling problems,a try and error-based scheduling algorithm was proposed with residency time constraints and an objective of minimizing Makespan for the wafer jobs in cluster tools.Firstly,mathematical formulations of scheduling problems were presented by using assumptions and definitions of a scheduling domain.Resource conflicts were analyzed in the built scheduling model,and policies to solve resource conflicts were built.A scheduling algorithm was developed.Finally,the performances of the proposed algorithm were evaluated and compared with those of other methods by simulations.Experiment results indicate that the proposed algorithm is effective and practical in solving the scheduling problem of the cluster tools.
文摘A hybrid feature selection and classification strategy was proposed based on the simulated annealing genetic algonthrn and multiple instance learning （MIL）. The band selection method was proposed from subspace decomposition, which combines the simulated annealing algorithm with the genetic algorithm in choosing different cross-over and mutation probabilities, as well as mutation individuals. Then MIL was combined with image segmentation, clustering and support vector machine algorithms to classify hyperspectral image. The experimental results show that this proposed method can get high classification accuracy of 93.13% at small training samples and the weaknesses of the conventional methods are overcome.
基金Project(71071052) supported by the National Natural Science Foundation of ChinaProject(JB2011097) supported by the Fundamental Research Funds for the Central Universities of China
文摘Accurate forecasting of wind velocity can improve the economic dispatch and safe operation of the power system. Support vector machine (SVM) has been proved to be an efficient approach for forecasting. According to the analysis with support vector machine method, the drawback of determining the parameters only by experts' experience should be improved. After a detailed description of the methodology of SVM and simulated annealing, an improved algorithm was proposed for the automatic optimization of parameters using SVM method. An example has proved that the proposed method can efficiently select the parameters of the SVM method. And by optimizing the parameters, the forecasting accuracy of the max wind velocity increases by 34.45%, which indicates that the new SASVM model improves the forecasting accuracy.
文摘According to time-sharing valuation principle (TSVP) of power supply, the relationships of current density and current efficiency at different acidities are obtained based on the processed data of electrolytic deposition process of zinc (EDPZ) with the least square method (LSM). Thus an optimal model of time-sharing power supply system for EDPZ is established, which has been optimized by use of an improved efficient simulated annealing algorithm (SAA). Practical results show that industrial and mining enterprises can obtain enormous economic benefits every year.
基金Project(E2015203354)supported by Natural Science Foundation of Steel United Research Fund of Hebei Province,ChinaProject(ZD2016100)supported by the Science and the Technology Research Key Project of High School of Hebei Province,China+1 种基金Project(LJRC013)supported by the University Innovation Team of Hebei Province Leading Talent Cultivation,ChinaProject(16LGY015)supported by the Basic Research Special Breeding of Yanshan University,China
文摘The accuracy of present flatness predictive method is limited and it just belongs to software simulation. In order to improve it, a novel flatness predictive model via T-S cloud reasoning network implemented by digital signal processor(DSP) is proposed. First, the combination of genetic algorithm(GA) and simulated annealing algorithm(SAA) is put forward, called GA-SA algorithm, which can make full use of the global search ability of GA and local search ability of SA. Later, based on T-S cloud reasoning neural network, flatness predictive model is designed in DSP. And it is applied to 900 HC reversible cold rolling mill. Experimental results demonstrate that the flatness predictive model via T-S cloud reasoning network can run on the hardware DSP TMS320 F2812 with high accuracy and robustness by using GA-SA algorithm to optimize the model parameter.
基金This project was supported by the National Natural Science Foundation (No. 69875010).
文摘A nonlinear visual mapping model is presented to replace the image Jacobian relation for uncalibrated hand/eye coordination. A new visual tracking controller based on artificial neural network is designed. Simulation results show that this method can drive the static tracking error to zero quickly and keep good robustness and adaptability at the same time. In addition, the algorithm is very easy to be implemented with low computational complexity.
