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完全零单半群的模糊同余(英文) 被引量:1
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作者 王喜建 《模糊系统与数学》 CSCD 北大核心 2007年第2期65-71,共7页
介绍完全零单半群上的真模糊同余和连接模糊三元组的概念,由此得到完全零单半群上的真模糊同余集和连接模糊三元组集之间的双射。
关键词 完全零单半群 关系 等价关系 同余 真同余 连接模三元组 正规模 糊子群
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Genetic algorithm and particle swarm optimization tuned fuzzy PID controller on direct torque control of dual star induction motor 被引量:13
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作者 BOUKHALFA Ghoulemallah BELKACEM Sebti +1 位作者 CHIKHI Abdesselem BENAGGOUNE Said 《Journal of Central South University》 SCIE EI CAS CSCD 2019年第7期1886-1896,共11页
This study presents analysis, control and comparison of three hybrid approaches for the direct torque control (DTC) of the dual star induction motor (DSIM) drive. Its objective consists of combining three different he... This study presents analysis, control and comparison of three hybrid approaches for the direct torque control (DTC) of the dual star induction motor (DSIM) drive. Its objective consists of combining three different heuristic optimization techniques including PID-PSO, Fuzzy-PSO and GA-PSO to improve the DSIM speed controlled loop behavior. The GA and PSO algorithms are developed and implemented into MATLAB. As a result, fuzzy-PSO is the most appropriate scheme. The main performance of fuzzy-PSO is reducing high torque ripples, improving rise time and avoiding disturbances that affect the drive performance. 展开更多
关键词 dual star induction motor drive direct torque control particle swarm optimization (PSO) fuzzy logic control genetic algorithms
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A Novel Particle Swarm Optimization for Flow Shop Scheduling with Fuzzy Processing Time 被引量:1
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作者 牛群 顾幸生 《Journal of Donghua University(English Edition)》 EI CAS 2008年第2期115-122,共8页
Since in most practical cases the processing time of scheduling is not deterministic, flow shop scheduling model with fuzzy processing time is established. It is assumed that the processing times of jobs on the machin... Since in most practical cases the processing time of scheduling is not deterministic, flow shop scheduling model with fuzzy processing time is established. It is assumed that the processing times of jobs on the machines are described by triangular fuzzy sets. In order to find a sequence that minimizes the mean makespan and the spread of the makespan, Lee and Li fuzzy ranking method is adopted and modified to solve the problem. Particle swarm optimization (PSO) is a population-based stochastic approximation algorithm that has been applied to a wide range of problems, but there is little reported in respect of application to scheduling problems because of its unsuitability for them. In the paper, PSO is redefined and modified by introducing genetic operations such as crossover and mutation to update the particles, which is called GPSO and successfully employed to solve the formulated problem. A series of benchmarks with fuzzy processing time are used to verify GPSO. Extensive experiments show the feasibility and effectiveness of the proposed method. 展开更多
关键词 flow shop SCHEDULING FUZZY PSO
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Fuzzy Ordered Filters in Implicative Semigroups
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作者 库热西 黄文平 《Chinese Quarterly Journal of Mathematics》 CSCD 1998年第2期53-57, ,共5页
We fuzzify the concept of ordered filter in implicative negatively partially ordered semigroups and study its properties.
关键词 implicative) negatively partially ordered semigroup ordered filter fuzzy ordered filter level ordered filter
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Combination forecast for urban rail transit passenger flow based on fuzzy information granulation and CPSO-LS-SVM 被引量:3
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作者 TANG Min-an ZHANG Kai LIU Xing 《Journal of Measurement Science and Instrumentation》 CAS CSCD 2018年第1期32-41,共10页
In order to obtain the trend of urban rail transit traffic flow and grasp the fluctuation range of passenger flow better,this paper proposes a combined forecasting model of passenger flow fluctuation range based on fu... In order to obtain the trend of urban rail transit traffic flow and grasp the fluctuation range of passenger flow better,this paper proposes a combined forecasting model of passenger flow fluctuation range based on fuzzy information granulation and least squares support vector machine(LS-SVM)optimized by chaos particle swarm optimization(CPSO).Due to the nonlinearity and fluctuation of the passenger flow,firstly,fuzzy information granulation is used to extract the valid data from the window according to the requirement.Secondly,CPSO that has strong global search ability is applied to optimize the parameters of the LS-SVM forecasting model.Finally,the combined model is used to forecast the fluctuation range of early peak passenger flow at Tiyu Xilu Station of Guangzhou Metro Line 3 in 2014,and the results are compared and analyzed with other models.Simulation results demonstrate that the combined forecasting model can effectively track the fluctuation of passenger flow,which provides an effective method for predicting the fluctuation range of short-term passenger flow in the future. 展开更多
关键词 urban rail transit passenger flow forecast least squares support vector machine(LS-SVM) fuzzy information granulation chaos particle swarm optimization(CPSO)
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Intelligent anti-swing control for bridge crane 被引量:2
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作者 陈志梅 孟文俊 张井岗 《Journal of Central South University》 SCIE EI CAS 2012年第10期2774-2781,共8页
A new intelligent anti-swing control scheme,which combined fuzzy neural network(FNN) and sliding mode control(SMC) with particle swarm optimization(PSO),was presented for bridge crane.The outputs of three fuzzy neural... A new intelligent anti-swing control scheme,which combined fuzzy neural network(FNN) and sliding mode control(SMC) with particle swarm optimization(PSO),was presented for bridge crane.The outputs of three fuzzy neural networks were used to approach the uncertainties of the positioning subsystem,lifting-rope subsystem and anti-swing subsystem.Then,the parameters of the controller were optimized with PSO to enable the system to have good dynamic performances.During the process of high-speed load hoisting and dropping,this method can not only realize the accurate position of the trolley and eliminate the sway of the load in spite of existing uncertainties,and the maximum swing angle is only ±0.1 rad,but also completely eliminate the chattering of conventional sliding mode control and improve the robustness of system.The simulation results show the correctness and validity of this method. 展开更多
关键词 bridge crane anti-swing control fuzzy neural network sliding mode control particle swarm optimization
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A Fuzzy Neural Network Model of Linguistic Dynamic Systems Based on Computing with Words
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作者 蔡国榕 李绍滋 +1 位作者 陈水利 吴云东 《Journal of Donghua University(English Edition)》 EI CAS 2010年第6期813-818,共6页
Linguistic dynamic systems(LDS)are dynamic processes involving computing with words(CW)for modeling and analysis of complex systems.In this paper,a fuzzy neural network(FNN)structure of LDS was proposed.In addition,an... Linguistic dynamic systems(LDS)are dynamic processes involving computing with words(CW)for modeling and analysis of complex systems.In this paper,a fuzzy neural network(FNN)structure of LDS was proposed.In addition,an improved nonlinear particle swarm optimization was employed for training FNN.The experiment results on logistics formulation demonstrates the feasibility and the efficiency of this FNN model. 展开更多
关键词 linguistic dynamic systems(LDS) computing with words(CW) fuzzy neural network(FNN) particle swarm optimization(PSO)
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Properties of Fuzzy M-Semigroups with t-Norms 被引量:1
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作者 詹建明 谭志松 《Journal of Mathematical Research and Exposition》 CSCD 北大核心 2006年第1期67-76,共10页
In this papr, we introduce the notion ofT-fuzzy M-subsemigroups of M-semigroups by using a t-norm T and obtain some interesting properties. Further we show that the direct product of a T-fuzzy M-subsemigroup of R and ... In this papr, we introduce the notion ofT-fuzzy M-subsemigroups of M-semigroups by using a t-norm T and obtain some interesting properties. Further we show that the direct product of a T-fuzzy M-subsemigroup of R and a fuzzy M-subsemigroup of S is a T-fuzzy M-subsemigroup of M, Moreover, we prove that T-fuzzy M-subsemigroup of M is exhibited as the direct product of T-fuzzy M-subsemigroups of R and S respectively. 展开更多
关键词 M-semigroups T-NORM (imaginable) T-fuzzy M-subsemigroups T-product.
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Homomorphisms between Two Sets of Fuzzy Subsemigroups *
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作者 李勇华 徐成贤 《Journal of Mathematical Research and Exposition》 CSCD 北大核心 2003年第4期615-622,共8页
Let S and T be semigroups. F(S) and F,(S) denote the sets of all fuzzy subsets and all fuzzy subsemigroups of 5, respectively. In this paper, we discuss the homomorphisms between F(S)(Fs(S)) and F(T)(Fs(T)). We introd... Let S and T be semigroups. F(S) and F,(S) denote the sets of all fuzzy subsets and all fuzzy subsemigroups of 5, respectively. In this paper, we discuss the homomorphisms between F(S)(Fs(S)) and F(T)(Fs(T)). We introduce the concept of fuzzy quotient subsemigroup and generalize the fundamental theorems of homomorphism of semigroups to fuzzy subsemigroups. 展开更多
关键词 fuzzy subsemigroup fuzzy quotient semigroup fuzzy congruence homo-morphism.
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Intuitionistic (S,T)-Fuzzy M-Subsemigroups of an M-Semigroup
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作者 马学玲 詹建明 《Journal of Mathematical Research and Exposition》 CSCD 北大核心 2007年第3期455-468,共14页
Intuitionistic fuzzy sets are generalized fuzzy sets which were first introduced by Atanassov in 1986. In this paper, we introduce the concept of intuitionistic fuzzy M-subsemigroups of an M-semigroup M with respect t... Intuitionistic fuzzy sets are generalized fuzzy sets which were first introduced by Atanassov in 1986. In this paper, we introduce the concept of intuitionistic fuzzy M-subsemigroups of an M-semigroup M with respect to an s-norm S and a t-norm T on in-tuitionistic fuzzy sets and study their properties. In particular, intuitionistic (S,T)-direct products of M-semigroups are considered and some recent results of fuzzy M-subsemigroups of M-semigroups obtained by Zhan and Tan^[21] are extended and generalized to intuitionistic (S, T)-fuzzy M-subsemigroups over M-semigroups. 展开更多
关键词 M-semigroup (imaginable) intuitionistic fuzzy M-subsemigroup intuitionistic(S T)-direct product.
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FUZZY EPQ INVENTORY MODELS WITH BACKORDER
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作者 Xiaobin WANG Wansheng TANG 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2009年第2期313-323,共11页
This paper considers the economic production quantity (EPQ) problem with backorder in which the setup cost, the holding cost and the backorder cost are characterized as fuzzy variables, respectively. Following expec... This paper considers the economic production quantity (EPQ) problem with backorder in which the setup cost, the holding cost and the backorder cost are characterized as fuzzy variables, respectively. Following expected value criterion and chance constrained criterion, a fuzzy expected value model (EVM) and a chance constrained programming (CCP) model are constructed. Then fuzzy simulations are employed to estimate the expected value of fuzzy variable and c^-level minimal average cost. In order to solve the CCP model, a particle swarm optimization (PSO) algorithm based on the fuzzy simulation is designed. Finally, the effectiveness of PSO algorithm based on the fuzzy simulation is illustrated by a numerical example. 展开更多
关键词 Economic production quantity fuzzy simulation fuzzy variable INVENTORY PSO.
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