 |
|
What people are saying - Write a reviewWe haven't found any reviews in the usual places. Related books
Common terms and phrasesadaptation algorithm applications approach approximation architecture Artificial Neural Networks chemostat classification complexity Computational Intelligence convergence Darwinian evolution data set data vectors defined developed dynamic environment equations error estimation evaluation evolutionary evolutionary algorithm example extended Kalman filter feature space Figure fitness fuzzy clusters fuzzy flip-flop fuzzy goals fuzzy logic fuzzy rules fuzzy sets fuzzy systems harvest rate hidden neurons hidden unit human humanoid IEEE input intelligent systems inverse kinematics joint velocity Kacprzyk Kansei knowledge layer learning linear lumberjacks mapping matrix measures membership functions method multi-NF system mutation neighbourhood system neocognitron neuro-fuzzy neurons neutral graph NF network nodes nonlinear occluded pattern ohtained on-line ontology operation optimization output parameters prediction problem Proc pruning recognition recurrent neural network redundant manipulators regression replicator robot RRBF network samples Science Soft Computing solution solve steady yield strings structure techniques Theorem values variables Popular passagesPage 379 - The label of a fuzzy set represents the name of a concept, and a fuzzy set represents the meaning of the concept. Therefore, the shape of a fuzzy set is determined by the meaning of the label, which depends on the situation (Fig.3). Page 179 - The variety of operators for the aggregation of fuzzy sets mentioned above might make it difficult to decide which one to use in a specific model or situation. Page 136 - T = {dO, ..., d8} which correspond, respectively, to clump thickness, uniformity of cell size, uniformity of cell shape, marginal adhesion, single epithelial cell size, bare nuclei, bland chromatin, normal nucleoli, and mitoses. Page 299 - ENGINEERING THE CHINESE UNIVERSITY OF HONG KONG SHATIN, NEW TERRITORIES, HONG KONG E-MAIL: JWANG@ACAE.CUHK.EDU.HK Recurrent neural networks are discussed for real-time inverse kinematic control of redundant manipulators. Page 210 - In the formula, ||xk - v,||2 represents the distance between the data xk and the cluster center v,. The squared error is used as a performance index that measures the weighted sum of distances between cluster centers and elements in the corresponding fuzzy clusters. The number m governs the influence of membership grades in the performance index. The partition becomes fuzzier with increasing m and it is proven that the FCMC algorithm converges for any me ( 1 ,Ť). The necessary conditions for (6)... Page 3 - artificial intelligence is the science of making machines do things that would require intelligence if done by men... Page 196 - J. Fodor, M. Roubens: Fuzzy Preference Modelling and Multicriteria Decision Support. Kluwer Academic Publishers, 1994, The Netherlands. Page 216 - Sugeno, M. A new method of choosing the number of clusters for fuzzy c-means method, in Proceedings of the 5th Fuzzy System Symposium. Page 197 - An Introductory Survey of Fuzzy Control," Inform. Sci., Vol. 36, pp. 59-83, 1985. References to this bookFrom Google Scholar基于双判据优化方法的机器人逆运动学求解张雨浓, 符刚, 尹江平 - 2007 - 大连海事大学学报: 自然科学版 References from web pagesMACHINE INTELLIGENCE: QUO VADIS? Quo Vadis, Computational Intelligence? (researchindex) Publications 2001 - 2004 Humanoid Robots Towards Learnable Technologies - Faculty of Informatics and Information Technologies Control Engineering Laboratory - Publications Machine Intelligence PUBLICATIONS Technická univerzita v Koiciach Fakulta elektrotechniky a ... Bibliographic information
|