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Titlebook: Advanced Fuzzy Systems Design and Applications; Yaochu Jin Book 2003 Springer-Verlag Berlin Heidelberg 2003 algorithms.artificial neural n

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发表于 2025-3-21 18:33:17 | 显示全部楼层 |阅读模式
期刊全称Advanced Fuzzy Systems Design and Applications
影响因子2023Yaochu Jin
视频video
发行地址Includes supplementary material:
学科分类Studies in Fuzziness and Soft Computing
图书封面Titlebook: Advanced Fuzzy Systems Design and Applications;  Yaochu Jin Book 2003 Springer-Verlag Berlin Heidelberg 2003 algorithms.artificial neural n
影响因子Fuzzy rule systems have found a wide range of applications in many fields of science and technology. Traditionally, fuzzy rules are generated from human expert knowledge or human heuristics for relatively simple systems. In the last few years, data-driven fuzzy rule generation has been very active. Compared to heuristic fuzzy rules, fuzzy rules generated from data are able to extract more profound knowledge for more complex systems. This book presents a number of approaches to the generation of fuzzy rules from data, ranging from the direct fuzzy inference based to neural net­ works and evolutionary algorithms based fuzzy rule generation. Besides the approximation accuracy, special attention has been paid to the interpretabil­ ity of the extracted fuzzy rules. In other words, the fuzzy rules generated from data are supposed to be as comprehensible to human beings as those generated from human heuristics. To this end, many aspects of interpretabil­ ity of fuzzy systems have been discussed, which must be taken into account in the data-driven fuzzy rule generation. In this way, fuzzy rules generated from data are intelligible to human users and therefore, knowledge about unknown syste
Pindex Book 2003
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Evolutionary Algorithms,gs, and between retained and distributed profits. The aim was to create equality and to use the tax regime as part of a ‘low effort bargain‘ that balanced wage restraint and low inflation against modest dividends. The tax regime favoured long-term, prudential savings in life insurance policies and p
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Artificial Neural Networks,nt and historical economic issues.Addresses the problems of Since the end of World War II, the Japanese economy has seen rapid changes and remarkable progress. It has also experienced a bubble economy and period of prolonged stagnation. The book seeks to address three major questions: What kind of c
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Fuzzy Knowledge Incorporation into Neural Networks,Atlantic Forest, with some exotic plant elements. Reforestation activities and conservationism require knowledge about pollination and seed production among native trees and shrubs adapted to local soil conditions. Besides other insects, birds, and bats, native Meliponini are significant pollinators
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Fuzzy Preferences Incorporation into Multi-objective Optimization,st geological epochs from the Cambrian to the present (Sonnenfeld 1985). The predominant mineral form is sylvite (KCl), found in almost every deposit with halite (NaCl) to form the mixture called sylvinite. In most occurrences fairly pure sylvinite exists with essentially no soluble sulfate or other
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https://doi.org/10.1007/978-3-663-13763-4e Knowledge through a process of learning and the acquired knowledge is stored in distribution among nodes and weights. Mathematically, most feed-forward neural networks are linear or non-linear function mapping systems that can perform function approximation (regression) and classification.
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