An analytical tuning method was proposed for fuzzy PID controller used in Smith predictor in order to extend its application and improve its robustness. The fuzzy PID controller was expressed as a sliding mode control...An analytical tuning method was proposed for fuzzy PID controller used in Smith predictor in order to extend its application and improve its robustness. The fuzzy PID controller was expressed as a sliding mode control. Based on Lyapunov theory, Smith predictor was analyzed in time domain. The parameters of the fuzzy PID controller can be obtained using traditional linear control theory and sliding mode control theory. The simulation experiments were implemented. The simulation results show that the control performance, robustness and stability of the fuzzy PID controller are better than those of the PID controller in Smith predictor.展开更多
In order to extract froth morphological feature,a bubble image adaptive segmentation method was proposed.Considering the image's low contrast and weak froth edges,froth image was coarsely segmented by using fuzzy ...In order to extract froth morphological feature,a bubble image adaptive segmentation method was proposed.Considering the image's low contrast and weak froth edges,froth image was coarsely segmented by using fuzzy c means(FCM) algorithm. Through the attributes of size and shape pattern spectrum,the optimal morphological structuring element was determined.According to the optimal parameters,some image noises were removed with an improved area opening and closing by reconstruction operation,which consist of image regional markers,and the bubbles were finely separated from each other by watershed transform.The experimental results show that the structural element can be determined adaptively by shape and size pattern spectrum,and the froth image is segmented accurately.Compared with other froth image segmentation method,the proposed method achieves much high accuracy,based on which,the bubble size and shape features are extracted effectively.展开更多
Based on the problem that the service entity only has the partial field of vision in the network environment,a trust evolvement method of the macro self-organization for Web service combination was proposed.In the met...Based on the problem that the service entity only has the partial field of vision in the network environment,a trust evolvement method of the macro self-organization for Web service combination was proposed.In the method,the control rule of the trust degree in the Dempster-Shafer(D-S)rule was utilized based on the entity network interactive behavior,and a proportion trust control rule was put up.The control rule could make the Web service self-adaptively study so as to gradually form a proper trust connection with its cooperative entities and to improve the security performance of the whole system.The experimental results show that the historical successful experience is saved during the service combination alliance,and the method can greatly improve the reliability and success rate of Web service combination.展开更多
As the huge computation and easily trapped local optimum in remanufacturing closed-loop supply chain network (RCSCN) design considered, a genetic particle swarm optimization algorithm was proposed. The total cost of c...As the huge computation and easily trapped local optimum in remanufacturing closed-loop supply chain network (RCSCN) design considered, a genetic particle swarm optimization algorithm was proposed. The total cost of closed-loop supply chain was selected as fitness function, and a unique and tidy coding mode was adopted in the proposed algorithm. Then, some mutation and crossover operators were introduced to achieve discrete optimization of RCSCN structure. The simulation results show that the proposed algorithm can gain global optimal solution with good convergent performance and rapidity. The computing speed is only 22.16 s, which is shorter than those of the other optimization algorithms.展开更多
Based on the deficiency of time convergence and variability of Web services selection for services composition supporting cross-enterprises collaboration,an algorithm QCDSS(QoS constraints of dynamic Web services sele...Based on the deficiency of time convergence and variability of Web services selection for services composition supporting cross-enterprises collaboration,an algorithm QCDSS(QoS constraints of dynamic Web services selection)to resolve dynamic Web services selection with QoS global optimal path,was proposed.The essence of the algorithm was that the problem of dynamic Web services selection with QoS global optimal path was transformed into a multi-objective services composition optimization problem with QoS constraints.The operations of the cross and mutation in genetic algorithm were brought into PSOA(particle swarm optimization algorithm),forming an improved algorithm(IPSOA)to solve the QoS global optimal problem.Theoretical analysis and experimental results indicate that the algorithm can better satisfy the time convergence requirement for Web services composition supporting cross-enterprises collaboration than the traditional algorithms.展开更多
To solve the problem of poor anti-noise performance of the traditional fuzzy C-means (FCM) algorithm in image segmentation, a novel two-dimensional FCM clustering algorithm for image segmentation was proposed. In this...To solve the problem of poor anti-noise performance of the traditional fuzzy C-means (FCM) algorithm in image segmentation, a novel two-dimensional FCM clustering algorithm for image segmentation was proposed. In this method, the image segmentation was converted into an optimization problem. The fitness function containing neighbor information was set up based on the gray information and the neighbor relations between the pixels described by the improved two-dimensional histogram. By making use of the global searching ability of the predator-prey particle swarm optimization, the optimal cluster center could be obtained by iterative optimization, and the image segmentation could be accomplished. The simulation results show that the segmentation accuracy ratio of the proposed method is above 99%. The proposed algorithm has strong anti-noise capability, high clustering accuracy and good segment effect, indicating that it is an effective algorithm for image segmentation.展开更多
The Circle algorithm was proposed for large datasets.The idea of the algorithm is to find a set of vertices that are close to each other and far from other vertices.This algorithm makes use of the connection between c...The Circle algorithm was proposed for large datasets.The idea of the algorithm is to find a set of vertices that are close to each other and far from other vertices.This algorithm makes use of the connection between clustering aggregation and the problem of correlation clustering.The best deterministic approximation algorithm was provided for the variation of the correlation of clustering problem,and showed how sampling can be used to scale the algorithms for large datasets.An extensive empirical evaluation was given for the usefulness of the problem and the solutions.The results show that this method achieves more than 50% reduction in the running time without sacrificing the quality of the clustering.展开更多
The study of induced polarization （IP） information extraction from magnetotelluric （MT） sounding data is of great and practical significance to the exploitation of deep mineral, oil and gas resources. The linear i...The study of induced polarization （IP） information extraction from magnetotelluric （MT） sounding data is of great and practical significance to the exploitation of deep mineral, oil and gas resources. The linear inversion method, which has been given priority in previous research on the IP information extraction method, has three main problems as follows： 1） dependency on the initial model, 2） easily falling into the local minimum, and 3） serious non-uniqueness of solutions. Taking the nonlinearity and nonconvexity of IP information extraction into consideration, a two-stage CO-PSO minimum structure inversion method using compute unified distributed architecture （CUDA） is proposed. On one hand, a novel Cauchy oscillation particle swarm optimization （CO-PSO） algorithm is applied to extract nonlinear IP information from MT sounding data, which is implemented as a parallel algorithm within CUDA computing architecture; on the other hand, the impact of the polarizability on the observation data is strengthened by introducing a second stage inversion process, and the regularization parameter is applied in the fitness function of PSO algorithm to solve the problem of multi-solution in inversion. The inversion simulation results of polarization layers in different strata of various geoelectric models show that the smooth models of resistivity and IP parameters can be obtained by the proposed algorithm, the results of which are relatively stable and accurate. The experiment results added with noise indicate that this method is robust to Gaussian white noise. Compared with the traditional PSO and GA algorithm, the proposed algorithm has more efficiency and better inversion results.展开更多
The problem of the stability analysis and controller design which the network-induced delays and data dropout problems network-induced delays are assumed to be time-varying and bounded, for Lurie networked control sys...The problem of the stability analysis and controller design which the network-induced delays and data dropout problems network-induced delays are assumed to be time-varying and bounded, for Lurie networked control systems （NCSs） is investigated, in are simultaneously considered. By considering that the and analyzing the relationship between the delay and its upper bound, employing a Lyapunov-Krasovskii function and an integral inequality approach, an improved stability criterion for NCSs is proposed. Furthermore, the resulting condition is extended to design a less conservative state feedback controller by employing an improved cone complementary linearization （ICCL） algorithm. Numerical examples are provided to show the effectiveness of the method.展开更多
基金Project(70473068) supported by the National Natural Science Foundation of ChinaProject(05JZD00024) supported by the Major Subject of Ministry of Education, China
文摘An analytical tuning method was proposed for fuzzy PID controller used in Smith predictor in order to extend its application and improve its robustness. The fuzzy PID controller was expressed as a sliding mode control. Based on Lyapunov theory, Smith predictor was analyzed in time domain. The parameters of the fuzzy PID controller can be obtained using traditional linear control theory and sliding mode control theory. The simulation experiments were implemented. The simulation results show that the control performance, robustness and stability of the fuzzy PID controller are better than those of the PID controller in Smith predictor.
基金Projects(60634020,60874069) supported by the National Natural Science Foundation of ChinaProject(2009AA04Z137) supported by the National High-Tech Research and Development Program of China
文摘In order to extract froth morphological feature,a bubble image adaptive segmentation method was proposed.Considering the image's low contrast and weak froth edges,froth image was coarsely segmented by using fuzzy c means(FCM) algorithm. Through the attributes of size and shape pattern spectrum,the optimal morphological structuring element was determined.According to the optimal parameters,some image noises were removed with an improved area opening and closing by reconstruction operation,which consist of image regional markers,and the bubbles were finely separated from each other by watershed transform.The experimental results show that the structural element can be determined adaptively by shape and size pattern spectrum,and the froth image is segmented accurately.Compared with other froth image segmentation method,the proposed method achieves much high accuracy,based on which,the bubble size and shape features are extracted effectively.
基金Project(60673169)supported by the National Natural Science Foundation of China
文摘Based on the problem that the service entity only has the partial field of vision in the network environment,a trust evolvement method of the macro self-organization for Web service combination was proposed.In the method,the control rule of the trust degree in the Dempster-Shafer(D-S)rule was utilized based on the entity network interactive behavior,and a proportion trust control rule was put up.The control rule could make the Web service self-adaptively study so as to gradually form a proper trust connection with its cooperative entities and to improve the security performance of the whole system.The experimental results show that the historical successful experience is saved during the service combination alliance,and the method can greatly improve the reliability and success rate of Web service combination.
基金Project(2011ZK2030)supported by the Soft Science Research Plan of Hunan Province,ChinaProject(2010ZDB42)supported by the Social Science Foundation of Hunan Province,China+1 种基金Projects(09A048,11B070)supported by the Science Research Foundation of Education Bureau of Hunan Province,ChinaProjects(2010GK3036,2011FJ6049)supported by the Science and Technology Plan of Hunan Province,China
文摘As the huge computation and easily trapped local optimum in remanufacturing closed-loop supply chain network (RCSCN) design considered, a genetic particle swarm optimization algorithm was proposed. The total cost of closed-loop supply chain was selected as fitness function, and a unique and tidy coding mode was adopted in the proposed algorithm. Then, some mutation and crossover operators were introduced to achieve discrete optimization of RCSCN structure. The simulation results show that the proposed algorithm can gain global optimal solution with good convergent performance and rapidity. The computing speed is only 22.16 s, which is shorter than those of the other optimization algorithms.
基金Project(70631004)supported by the Key Project of the National Natural Science Foundation of ChinaProject(20080440988)supported by the Postdoctoral Science Foundation of China+1 种基金Project(09JJ4030)supported by the Natural Science Foundation of Hunan Province,ChinaProject supported by the Postdoctoral Science Foundation of Central South University,China
文摘Based on the deficiency of time convergence and variability of Web services selection for services composition supporting cross-enterprises collaboration,an algorithm QCDSS(QoS constraints of dynamic Web services selection)to resolve dynamic Web services selection with QoS global optimal path,was proposed.The essence of the algorithm was that the problem of dynamic Web services selection with QoS global optimal path was transformed into a multi-objective services composition optimization problem with QoS constraints.The operations of the cross and mutation in genetic algorithm were brought into PSOA(particle swarm optimization algorithm),forming an improved algorithm(IPSOA)to solve the QoS global optimal problem.Theoretical analysis and experimental results indicate that the algorithm can better satisfy the time convergence requirement for Web services composition supporting cross-enterprises collaboration than the traditional algorithms.
基金Project(06JJ50110) supported by the Natural Science Foundation of Hunan Province, China
文摘To solve the problem of poor anti-noise performance of the traditional fuzzy C-means (FCM) algorithm in image segmentation, a novel two-dimensional FCM clustering algorithm for image segmentation was proposed. In this method, the image segmentation was converted into an optimization problem. The fitness function containing neighbor information was set up based on the gray information and the neighbor relations between the pixels described by the improved two-dimensional histogram. By making use of the global searching ability of the predator-prey particle swarm optimization, the optimal cluster center could be obtained by iterative optimization, and the image segmentation could be accomplished. The simulation results show that the segmentation accuracy ratio of the proposed method is above 99%. The proposed algorithm has strong anti-noise capability, high clustering accuracy and good segment effect, indicating that it is an effective algorithm for image segmentation.
基金Projects(60873265,60903222) supported by the National Natural Science Foundation of China Project(IRT0661) supported by the Program for Changjiang Scholars and Innovative Research Team in University of China
文摘The Circle algorithm was proposed for large datasets.The idea of the algorithm is to find a set of vertices that are close to each other and far from other vertices.This algorithm makes use of the connection between clustering aggregation and the problem of correlation clustering.The best deterministic approximation algorithm was provided for the variation of the correlation of clustering problem,and showed how sampling can be used to scale the algorithms for large datasets.An extensive empirical evaluation was given for the usefulness of the problem and the solutions.The results show that this method achieves more than 50% reduction in the running time without sacrificing the quality of the clustering.
基金Projects(41604117,41204054)supported by the National Natural Science Foundation of ChinaProjects(20110490149,2015M580700)supported by the Research Fund for the Doctoral Program of Higher Education,China+1 种基金Project(2015zzts064)supported by the Fundamental Research Funds for the Central Universities,ChinaProject(16B147)supported by the Scientific Research Fund of Hunan Provincial Education Department,China
文摘The study of induced polarization （IP） information extraction from magnetotelluric （MT） sounding data is of great and practical significance to the exploitation of deep mineral, oil and gas resources. The linear inversion method, which has been given priority in previous research on the IP information extraction method, has three main problems as follows： 1） dependency on the initial model, 2） easily falling into the local minimum, and 3） serious non-uniqueness of solutions. Taking the nonlinearity and nonconvexity of IP information extraction into consideration, a two-stage CO-PSO minimum structure inversion method using compute unified distributed architecture （CUDA） is proposed. On one hand, a novel Cauchy oscillation particle swarm optimization （CO-PSO） algorithm is applied to extract nonlinear IP information from MT sounding data, which is implemented as a parallel algorithm within CUDA computing architecture; on the other hand, the impact of the polarizability on the observation data is strengthened by introducing a second stage inversion process, and the regularization parameter is applied in the fitness function of PSO algorithm to solve the problem of multi-solution in inversion. The inversion simulation results of polarization layers in different strata of various geoelectric models show that the smooth models of resistivity and IP parameters can be obtained by the proposed algorithm, the results of which are relatively stable and accurate. The experiment results added with noise indicate that this method is robust to Gaussian white noise. Compared with the traditional PSO and GA algorithm, the proposed algorithm has more efficiency and better inversion results.
基金Project(61025015)supported by the National Natural Science Foundation of China for Distinguished Young ScholarsProject (IRT1044)supported by the Program for Changjiang Scholars and Innovative Research Team in University of China+2 种基金Projects(61143004,61203136,61074067,61273185)supported by the National Natural Science Foundation of ChinaProjects(12JJ4062,11JJ2033)supported by the Natural Science Foundation of Hunan Province,ChinaProject(12C0078)supported by Hunan Provincial Department of Education,China
文摘The problem of the stability analysis and controller design which the network-induced delays and data dropout problems network-induced delays are assumed to be time-varying and bounded, for Lurie networked control systems （NCSs） is investigated, in are simultaneously considered. By considering that the and analyzing the relationship between the delay and its upper bound, employing a Lyapunov-Krasovskii function and an integral inequality approach, an improved stability criterion for NCSs is proposed. Furthermore, the resulting condition is extended to design a less conservative state feedback controller by employing an improved cone complementary linearization （ICCL） algorithm. Numerical examples are provided to show the effectiveness of the method.
