Run time adaptation of UMTS services to available resources； Self-learning fuzzy sliding-mode control for antilock braking systems； Simulated and experimental study of hydraulic anti-lock braking system using slidin...Run time adaptation of UMTS services to available resources； Self-learning fuzzy sliding-mode control for antilock braking systems； Simulated and experimental study of hydraulic anti-lock braking system using sliding-mode PWM control；Sliding mode control on electro-mechanical systems； SMB block copolymers, or the power of nanostructuration； The study of the stiction free magnetic recording head with DLC pad -the optimization of DLC pad and ABS展开更多
The trained Gaussian mixture model is used to make skincolour segmentation for the input image sequences. The hand gesture region is extracted, and the relative normalization images are obtained by interpolation opera...The trained Gaussian mixture model is used to make skincolour segmentation for the input image sequences. The hand gesture region is extracted, and the relative normalization images are obtained by interpolation operation. To solve the proem of hand gesture recognition, Fuzzy-Rough based nearest neighbour（RNN） algorithm is applied for classification. For avoiding the costly compute, an improved nearest neighbour classification algorithm based on fuzzy-rough set theory （FRNNC） is proposed. The algorithm employs the represented cluster points instead of the whole training samples, and takes the hand gesture data＇s fuzziness and the roughness into account, so the campute spending is decreased and the recognition rate is increased. The 30 gestures in Chinese sign language alphabet are used for approving the effectiveness of the proposed algorithm. The recognition rate is 94.96%, which is better than that of KNN （K nearest neighbor）and Fuzzy- KNN （Fuzzy K nearest neighbor）.展开更多
In the course of running an artificial intelligent system many redundant rules are often produced. To refine the knowledge base, viz. to remove the redundant rules, can accelerate the reasoning and shrink the rule bas...In the course of running an artificial intelligent system many redundant rules are often produced. To refine the knowledge base, viz. to remove the redundant rules, can accelerate the reasoning and shrink the rule base. The purpose of the paper is to present the thinking on the topic and design the algorithm to remove the redundant rules from the rule base. The “abstraction” of “state variable”, redundant rules and the least rule base are discussed in the paper. The algorithm on refining knowledge base is also presented.展开更多
The paper follows possible specification of a control algorithm of a WS （water management system） during floods using the procedures of AI （artificial intelligence）. The issue of minimizing negative impacts of flo...The paper follows possible specification of a control algorithm of a WS （water management system） during floods using the procedures of AI （artificial intelligence）. The issue of minimizing negative impacts of floods represents influencing and controlling a dynamic process of the system where the main regulation elements are water reservoirs. Control of water outflow from reservoirs is implicitly based on the used model （titled BW） based on FR （fuzzy regulation）. Specification of a control algorithm means dealing with the issue of preparing a knowledge base for the process of tuning fuzzy regulators based on an I/O （input/output） matrix obtained by optimization of the target behaviour of WS. Partial results can be compared with the regulation outputs when specialized tuning was used for the fuzzy regulator of the control algorithm. Basic approaches follow from the narrow relation on BW model use to simulate floods, without any connection to real water management system. A generally introduced model allows description of an outflow dynamic system with stochastic inputs using submodels of robust regression in the outflow module. The submodels are constructed on data of historical FS （flood situations）.展开更多
The fuzzy logic, which is a technique of the artificial intelligence, rises as a result of studies based on simulating the human brain. It is a type of logic that recognizes more than simple true and false values. Lin...The fuzzy logic, which is a technique of the artificial intelligence, rises as a result of studies based on simulating the human brain. It is a type of logic that recognizes more than simple true and false values. Linguistic variables can be represented with degrees of truthfulness and falsehood by using fuzzy logic. Like other artificial intelligence techniques, the fuzzy logic is used in many different areas. In computer game industry, it can be used to develop artificial intelligence based games. In this paper, the author discusses about usage of the fuzzy logic technique in computer games and developed a basic game based on the fuzzy logic. In this game, a computer controlled character can behave differently according to changing situations.展开更多
文摘Run time adaptation of UMTS services to available resources； Self-learning fuzzy sliding-mode control for antilock braking systems； Simulated and experimental study of hydraulic anti-lock braking system using sliding-mode PWM control；Sliding mode control on electro-mechanical systems； SMB block copolymers, or the power of nanostructuration； The study of the stiction free magnetic recording head with DLC pad -the optimization of DLC pad and ABS
文摘The trained Gaussian mixture model is used to make skincolour segmentation for the input image sequences. The hand gesture region is extracted, and the relative normalization images are obtained by interpolation operation. To solve the proem of hand gesture recognition, Fuzzy-Rough based nearest neighbour（RNN） algorithm is applied for classification. For avoiding the costly compute, an improved nearest neighbour classification algorithm based on fuzzy-rough set theory （FRNNC） is proposed. The algorithm employs the represented cluster points instead of the whole training samples, and takes the hand gesture data＇s fuzziness and the roughness into account, so the campute spending is decreased and the recognition rate is increased. The 30 gestures in Chinese sign language alphabet are used for approving the effectiveness of the proposed algorithm. The recognition rate is 94.96%, which is better than that of KNN （K nearest neighbor）and Fuzzy- KNN （Fuzzy K nearest neighbor）.
基金Supported by the National Education Science Foundation of China under Grant(No.104086)
文摘In the course of running an artificial intelligent system many redundant rules are often produced. To refine the knowledge base, viz. to remove the redundant rules, can accelerate the reasoning and shrink the rule base. The purpose of the paper is to present the thinking on the topic and design the algorithm to remove the redundant rules from the rule base. The “abstraction” of “state variable”, redundant rules and the least rule base are discussed in the paper. The algorithm on refining knowledge base is also presented.
文摘The paper follows possible specification of a control algorithm of a WS （water management system） during floods using the procedures of AI （artificial intelligence）. The issue of minimizing negative impacts of floods represents influencing and controlling a dynamic process of the system where the main regulation elements are water reservoirs. Control of water outflow from reservoirs is implicitly based on the used model （titled BW） based on FR （fuzzy regulation）. Specification of a control algorithm means dealing with the issue of preparing a knowledge base for the process of tuning fuzzy regulators based on an I/O （input/output） matrix obtained by optimization of the target behaviour of WS. Partial results can be compared with the regulation outputs when specialized tuning was used for the fuzzy regulator of the control algorithm. Basic approaches follow from the narrow relation on BW model use to simulate floods, without any connection to real water management system. A generally introduced model allows description of an outflow dynamic system with stochastic inputs using submodels of robust regression in the outflow module. The submodels are constructed on data of historical FS （flood situations）.
文摘The fuzzy logic, which is a technique of the artificial intelligence, rises as a result of studies based on simulating the human brain. It is a type of logic that recognizes more than simple true and false values. Linguistic variables can be represented with degrees of truthfulness and falsehood by using fuzzy logic. Like other artificial intelligence techniques, the fuzzy logic is used in many different areas. In computer game industry, it can be used to develop artificial intelligence based games. In this paper, the author discusses about usage of the fuzzy logic technique in computer games and developed a basic game based on the fuzzy logic. In this game, a computer controlled character can behave differently according to changing situations.
