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A Knowledge Context Fuzzy Clustering Method Based on Genetic Algorithm

Faping Zhang, Li Li, Cuixiang Zhou, Bing Xu, Yinong Chen
2017 MATEC Web of Conferences  
A fuzzy clustering method based on genetic algorithm is proposed aiming at the problem of automatic clustering of knowledge context.  ...  Then the fuzzy C mean clustering result is solved by genetic algorithm, and the clustering of knowledge context is realized.  ...  Aiming at the clustering problem of knowledge context, this paper proposes a knowledge context fuzzy clustering method based on genetic algorithm.  ... 
doi:10.1051/matecconf/201713900064 fatcat:rsuwthuz6bcdxgzvso7zuvhr6i

Fuzzy decision support system knowledge base generation using a genetic algorithm

Luc Baron, Sofiane Achiche, Marek Balazinski
2001 International Journal of Approximate Reasoning  
This paper presents a genetic algorithm (GA) that automatically constructs the knowledge base used by fuzzy decision support systems (FDSS).  ...  This knowledge base is composed of the minimum number of fuzzy sets and rules.  ...  However, we have presented, in this paper, a genetic algorithm that can automatically construct a knowledge base.  ... 
doi:10.1016/s0888-613x(01)00047-0 fatcat:r3p66fhuhjhihat6yg5ox3p4dy

Multi-objective hierarchical genetic algorithm for interpretable fuzzy rule-based knowledge extraction

Hanli Wang, Sam Kwong, Yaochu Jin, Wei Wei, K.F. Man
2005 Fuzzy sets and systems (Print)  
A new scheme based on multi-objective hierarchical genetic algorithm (MOHGA) is proposed to extract interpretable rule-based knowledge from data.  ...  Then the multi-objective hierarchical genetic algorithm and the recursive least square method are used to obtain the optimized fuzzy models.  ...  Multiobjective hierarchical genetic algorithm and interpretability-driven rule base simplification method In this section, we will discuss how to use the multi-objective hierarchical genetic algorithm  ... 
doi:10.1016/j.fss.2004.07.013 fatcat:45wta7iwsvd3fgido5n6eotuv4

A new approach for tuning interval type-2 fuzzy knowledge bases using genetic algorithms

Praveen Kumar Shukla, Surya Prakash Tripathi
2014 Journal of Uncertainty Analysis and Applications  
Fuzzy knowledge-based systems (FKBS) are significantly applicable in the area of control, classification, and modeling, having knowledge in the form of fuzzy if-then rules.  ...  In this paper, the authors have proposed a genetic tuning approach named lateral displacement and expansion/compression (LDEC) in which α and β parameters are calculated to adjust the parameters of interval  ...  The genetic representation of KB and the proposed tuning approach is discussed in the 'Genetic representation of knowledge base' section.  ... 
doi:10.1186/2195-5468-2-4 fatcat:4nekk55zlvh75p3qvyovgqq4xi

A MULTI-OBJECTIVE GENETIC ALGORITHM FOR TUNING AND RULE SELECTION TO OBTAIN ACCURATE AND COMPACT LINGUISTIC FUZZY RULE-BASED SYSTEMS

R. ALCALÁ, M. J. GACTO, F. HERRERA, J. ALCALÁ-FDEZ
2007 International Journal of Uncertainty Fuzziness and Knowledge-Based Systems  
This work proposes the application of Multi-Objective Genetic Algorithms to obtain Fuzzy Rule-Based Systems with a better trade-off between interpretability and accuracy in linguistic fuzzy modelling problems  ...  This method is based on the well-known SPEA2 algorithm, applying appropriate genetic operators and including some modifications to concentrate the search in the desired Pareto zone.  ...  In this contribution, we focus on this problem by using Genetic Algorithms as a tool for evolving the MFs parameters and rule base size and by coding all of them (rules and parameters) in the same chromosome  ... 
doi:10.1142/s0218488507004868 fatcat:ci6kslhhvbfihbwjg5i6jldcma

A Proposal of Knowledge-Based Systems Using Fuzzy Rules and Genetic Algorithms
ファジィルールと遺伝的アルゴリズムを用いた知識ベースシステムの一提案

Andreas BASTIAN, Isao HAYASHI
1996 Journal of Japan Society for Fuzzy Theory and Systems  
Based Systems Using Fuzzy Rules and Genetic Algorithms Andreas BASTIAN and Isao HAYASHI * 1フ ォ ル ク ス ワ ー ゲ ン 電予 研 究 所 Electronic Research, 1776, Volkswagen AG * 2 阪南 大 学 経 営 情 報 学 部 経 営 情 報 学 科 Department  ...  Keywords : Genetic Algorithm, Fuzzy Rules, Fuzzy Control, Tuning Problem Conta¢ t Address I Andreas BASTIAN EIectroi2ic Researcit, 1776, Vogksu.  ... 
doi:10.3156/jfuzzy.8.6_76 fatcat:2ucoycocwvdlreeu7qmn7xnh5y

Real/binary-like coded versus binary coded genetic algorithms to automatically generate fuzzy knowledge bases: a comparative study

Sofiane Achiche, Luc Baron, Marek Balazinski
2004 Engineering applications of artificial intelligence  
This paper presents the implementation of a combination of a Real/Binary-Like coded Genetic Algorithm (RBLGA) and a Binary coded Genetic Algorithm (BGA) to automatically generate Fuzzy Knowledge Bases  ...  and (2) a binary like coded genetic algorithm that deals with the fuzzy rule base relationships (a set of integers).  ...  Automatic generation of fuzzy knowledge bases using GAs The automatic generation of fuzzy knowledge bases is performed using a GA.  ... 
doi:10.1016/j.engappai.2004.04.006 fatcat:4y3bamamenhjzdybwqto3u3uuu

Using Fuzzy Cognitive Maps for Prediction of Knowledge Worker Productivity Based on Real Coded Genetic Algorithm

Asadallah Najafi, Abbas Afrazeh
2011 International Journal of Industrial Engineering and Production Research  
time based on the Fuzzy cognitive maps (FCM) technique Based on Real Coded Genetic Algorithm (RCGA) , as well as presenting the best option from among different options as the knowledge workers' productivity  ...  improving strategy (suggesting solution), based on the results gained from this and the previous section and depending on the requirements.  ...  Recently, they introduced genetic optimization based learning algorithm (genetic algorithm) allows for automatic expanding of the Fuzzy Cognetive Maps from the genetic data.  ... 
doaj:f48ddf1e056843288075c38fa8b93dce fatcat:65qhk3l6sbcojhmo6ti5dyas4q

Optimal control of asynchronous motor mechanical efficiency based on genetic algorithms

Shouguang Li, Huikang Liu
2010 2010 Sixth International Conference on Natural Computation  
to realize the accurate linearization of model with controllable power loss and high-precision tracking and control of speed and flux linkage of rotor through the state feedback precise linearization algorithm  ...  Results show that through state feedback exact linearization algorithm of MIMO system, the accurate linearization of affine nonlinear motor model and the dynamic decoupling of output variable can be realized  ...  This paper aims at the motor efficiency for the first time, and uses the feedback linearization method based on the differential geometric principle for control of energy consumption model of motor and  ... 
doi:10.1109/icnc.2010.5583513 dblp:conf/icnc/LiL10b fatcat:lys4g477yzfklgyccqluiw775e

The Convergence Analysis of Genetic Algorithm Based on Space Mating

Hui Lv, Jinghua Zheng, Jun Wu, Cong Zhou, Ke Li
2009 2009 Fifth International Conference on Natural Computation  
It is proved by means of homogeneous finite Markov chain analysis that genetic algorithm based on space mating will converge to the global optimum.  ...  This paper analyzes the convergence properties of the genetic algorithm based on space mating with mutation, crossover and proportional reproduction applied to static optimization on problems.  ...  GENETIC ALGORITHM BASED ON SPACE MATING The Algorithm Genetic algorithm based on space mating start-up the number of n parallel Process at the beginning.  ... 
doi:10.1109/icnc.2009.39 dblp:conf/icnc/LvZWZL09 fatcat:eq4sbvrixvbidg5j4av6ro4z2m

Parameter Identification of Hydro Generation System with Fluid Transients Based on Improved Genetic Algorithm

Lin Gao, Yiping Dai, Junrong Xia
2009 2009 Fifth International Conference on Natural Computation  
An improved genetic algorithm is proposed in this paper to estimate the parameters of a hydro generation system model which contains a series of basic differential equations to represent the flow transients  ...  Improved Genetic Algorithm A Genetic Algorithm (GA) represents a heuristic search technique based on the evolutionary ideas of natural selection and genetics.  ...  Method based on Genetic Algorithm (GA) which is inspired by the mechanism of natural selection is proposed to identify both linear and nonlinear models.  ... 
doi:10.1109/icnc.2009.23 dblp:conf/icnc/GaoDX09 fatcat:2ar5wm43uvgnlnaudxz7vlqfgi

A Multiple Evolutionary Neural Network Classifier Based on Niche Genetic Algorithm

Jiang Wu, Changjie Tang, Taiyong Li, Yue Jiang, Shangyu Ye, Xun Lin, Jie Zuo
2008 2008 Fourth International Conference on Natural Computation  
The neural networks are trained by niche genetic algorithm based on clustering.  ...  In this paper, a Multiple Evolutionary Neural Network Classifier Based on Niche Genetic Algorithm (MNC-NG) is presented, which establishes classifiers by a group of three-layer feed-forward neural networks  ...  The neural networks are trained by niche genetic algorithm based on clustering.  ... 
doi:10.1109/icnc.2008.602 dblp:conf/icnc/WuTLJYLZ08 fatcat:oajqic74crbzhpsfxj53zsjkui

Optimizing fuzzy knowledge base by genetic algorithms and neural networks

E.C.C. Tsang, D.S. Yeung
IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028)  
The iterative, repeated and painstaking task of consulting with domain experts to obtain, tune and update the fuzzy knowledge base is greatly reduced.  ...  To draw an accurate, reasonable and reliable conclusion in a fuzzy expert system, the knowledge base plays an important role and is the heart of this system.  ...  Genetic Algorithm Approach Genetic algorithms were proposed by Holland [ 131 to solve those searching and optimisation problems.  ... 
doi:10.1109/icsmc.1999.823232 fatcat:w5kvbx6cl5a6lagc7oadn7ju5i

Genetic Fuzzy Systems: Evolutionary Tuning and Learning of Fuzzy Knowledge Bases, Algorithms and Fuzzy Systems

O Cordón, F Herrera, F Hoffmann, & Magdalena, L Zadeh
2009 IEEE Transactions on Systems, Man, and Cybernetics   unpublished
In this study, two methods of fuzzy clustering and genetic algorithm were employed to build fuzzy knowledge base automatically.  ...  The results indicated that knowledge base extracted by genetic algorithm with RMSE of 4 had better accuracy than fuzzy clustering.  ...  In this study, two methods of fuzzy clustering and genetic algorithm were employed to build fuzzy knowledge base automatically.  ... 
fatcat:iqlmqj67rneyhec3fiwk7f5vdu

Genetic Fuzzy Systems: Evolutionary Tuning and Learning of Fuzzy Knowledge Bases, Algorithms and Fuzzy Systems

O Cordón, F Herrera, F Hoffmann, & Magdalena, F Herrera, M Lozano, Verdegay, F Hosseinali, C James, Robert Bezdek, & Ehrlich, Full (+1 others)
2009 IEEE Transactions on Systems, Man, and Cybernetics   unpublished
In this study, two methods of fuzzy clustering and genetic algorithm were employed to build fuzzy knowledge base automatically.  ...  The results indicated that knowledge base extracted by genetic algorithm with RMSE of 4 had better accuracy than fuzzy clustering.  ...  In this study, two methods of fuzzy clustering and genetic algorithm were employed to build fuzzy knowledge base automatically.  ... 
fatcat:m6rvna6mvretxftucah3mmpdmq
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