By constructing a mcan-square performance index in the case of fuzzy random variable, the optimal estimation theorem for unknown fuzzy state using the fuzzy observation data are given. The state and output of linear d...By constructing a mcan-square performance index in the case of fuzzy random variable, the optimal estimation theorem for unknown fuzzy state using the fuzzy observation data are given. The state and output of linear discrete-time dynamic fuzzy system with Gaussian noise are Gaussian fuzzy random variable sequences. An approach to fuzzy Kalman filtering is discussed. Fuzzy Kalman filtering contains two parts： a real-valued non-random recurrence equation and the standard Kalman filtering.展开更多
Semiconductor manufacturing (SM) system is one of the most complicated hybrid processes involved continuously variable dynamical systems and discrete event dynamical systems. The optimization and scheduling of semicon...Semiconductor manufacturing (SM) system is one of the most complicated hybrid processes involved continuously variable dynamical systems and discrete event dynamical systems. The optimization and scheduling of semiconductor fabrication has long been a hot research direction in automation. Bottleneck is the key factor to a SM system, which seriously influences the throughput rate, cycle time, time-delivery rate, etc. Efficient prediction for the bottleneck of a SM system provides the best support for the consequent scheduling. Because categorical data (product types, releasing strategies) and numerical data (work in process, processing time, utilization rate, buffer length, etc.) have significant effect on bottleneck, an improved adaptive network-based fuzzy inference system (ANFIS) was adopted in this study to predict bottleneck since conventional neural network-based methods accommodate only numerical inputs. In this improved ANFIS, the contribution of categorical inputs to firing strength is reflected through a transformation matrix. In order to tackle high-dimensional inputs, reduce the number of fuzzy rules and obtain high prediction accuracy, a fuzzy c-means method combining binary tree linear division method was applied to identify the initial structure of fuzzy inference system. According to the experimental results, the main-bottleneck and sub-bottleneck of SM system can be predicted accurately with the proposed method.展开更多
The remain passenger problem at subway station platform was defined initially,and the period variation of remain passenger queues at platform was investigated through arriving and boarding analyses.Taking remain passe...The remain passenger problem at subway station platform was defined initially,and the period variation of remain passenger queues at platform was investigated through arriving and boarding analyses.Taking remain passenger queues at platform as dynamic stochastic process,a new probabilistic queuing method was developed based on probabilistic theory and discrete time Markov chain theory.This model can calculate remain passenger queues while considering different directions.Considering the stable or variable train arriving period and different platform crossing types,a series of model deformation research was carried out.The probabilistic approach allows to capture the cyclic behavior of queues,measures the uncertainty of a queue state prediction by computing the evolution of its probability in time,and gives any temporal distribution of the arrivals.Compared with the actual data,the deviation of experimental results is less than 20%,which shows the efficiency of probabilistic approach clearly.展开更多
Human behavioral responses fundamentally influence the spread of infectious disease. In this paper, we study a discrete-time SIS epidemic process in random networks. Three forms of individual awareness, namely, local ...Human behavioral responses fundamentally influence the spread of infectious disease. In this paper, we study a discrete-time SIS epidemic process in random networks. Three forms of individual awareness, namely, local awareness, global awareness and contact awareness, are considered. The effect of awareness is to reduce the risk of infection. [3ased on the stability theory of matrix difference equation, we derive analytically the epidemic threshold. It is found that both local and contact awareness can raise the epidemic threshold, while the global awareness only decreases the epidemic prevalence. Our results are in line with a recent result using differential equation-based methods.展开更多
基金Project 60374022 supported by the National Natural Science Foundation of China.
文摘By constructing a mcan-square performance index in the case of fuzzy random variable, the optimal estimation theorem for unknown fuzzy state using the fuzzy observation data are given. The state and output of linear discrete-time dynamic fuzzy system with Gaussian noise are Gaussian fuzzy random variable sequences. An approach to fuzzy Kalman filtering is discussed. Fuzzy Kalman filtering contains two parts： a real-valued non-random recurrence equation and the standard Kalman filtering.
基金Supported by the National Key Basic Research and Development Program of China (2009CB320602)the National Natural Science Foundation of China (60834004, 61025018)+2 种基金the Open Project Program of the State Key Lab of Industrial ControlTechnology (ICT1108)the Open Project Program of the State Key Lab of CAD & CG (A1120)the Foundation of Key Laboratory of System Control and Information Processing (SCIP2011005),Ministry of Education,China
文摘Semiconductor manufacturing (SM) system is one of the most complicated hybrid processes involved continuously variable dynamical systems and discrete event dynamical systems. The optimization and scheduling of semiconductor fabrication has long been a hot research direction in automation. Bottleneck is the key factor to a SM system, which seriously influences the throughput rate, cycle time, time-delivery rate, etc. Efficient prediction for the bottleneck of a SM system provides the best support for the consequent scheduling. Because categorical data (product types, releasing strategies) and numerical data (work in process, processing time, utilization rate, buffer length, etc.) have significant effect on bottleneck, an improved adaptive network-based fuzzy inference system (ANFIS) was adopted in this study to predict bottleneck since conventional neural network-based methods accommodate only numerical inputs. In this improved ANFIS, the contribution of categorical inputs to firing strength is reflected through a transformation matrix. In order to tackle high-dimensional inputs, reduce the number of fuzzy rules and obtain high prediction accuracy, a fuzzy c-means method combining binary tree linear division method was applied to identify the initial structure of fuzzy inference system. According to the experimental results, the main-bottleneck and sub-bottleneck of SM system can be predicted accurately with the proposed method.
基金Project(2011BAG01B01) supported by the Major State Basic Research and Development Program of ChinaProject(RCS2012ZZ002) supported by the State Key Lab of Rail Traffic Control and Safety,China
文摘The remain passenger problem at subway station platform was defined initially,and the period variation of remain passenger queues at platform was investigated through arriving and boarding analyses.Taking remain passenger queues at platform as dynamic stochastic process,a new probabilistic queuing method was developed based on probabilistic theory and discrete time Markov chain theory.This model can calculate remain passenger queues while considering different directions.Considering the stable or variable train arriving period and different platform crossing types,a series of model deformation research was carried out.The probabilistic approach allows to capture the cyclic behavior of queues,measures the uncertainty of a queue state prediction by computing the evolution of its probability in time,and gives any temporal distribution of the arrivals.Compared with the actual data,the deviation of experimental results is less than 20%,which shows the efficiency of probabilistic approach clearly.
文摘Human behavioral responses fundamentally influence the spread of infectious disease. In this paper, we study a discrete-time SIS epidemic process in random networks. Three forms of individual awareness, namely, local awareness, global awareness and contact awareness, are considered. The effect of awareness is to reduce the risk of infection. [3ased on the stability theory of matrix difference equation, we derive analytically the epidemic threshold. It is found that both local and contact awareness can raise the epidemic threshold, while the global awareness only decreases the epidemic prevalence. Our results are in line with a recent result using differential equation-based methods.
