Titlebook: Hybrid Intelligent Systems; Larry R. Medsker Book 1995 Kluwer Academic Publishers 1995 adaptive control.algorithms.case-based reasoning.co

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書目名稱Hybrid Intelligent Systems影響因子(影響力)




書目名稱Hybrid Intelligent Systems影響因子(影響力)學(xué)科排名




書目名稱Hybrid Intelligent Systems網(wǎng)絡(luò)公開度




書目名稱Hybrid Intelligent Systems網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Hybrid Intelligent Systems被引頻次




書目名稱Hybrid Intelligent Systems被引頻次學(xué)科排名




書目名稱Hybrid Intelligent Systems年度引用




書目名稱Hybrid Intelligent Systems年度引用學(xué)科排名




書目名稱Hybrid Intelligent Systems讀者反饋




書目名稱Hybrid Intelligent Systems讀者反饋學(xué)科排名

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Expert Networks: Theory and Applications, major thrust of this type of hybrid system is to synthesize the capability of expert systems to capture expert domain knowledge in an inference-based system with the power of black-box neural networks trained from example data.

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Fuzzy Systems and Neural Networks,ns are starting to be developed. A natural integration follows the same successful path of hybrid neural network and expert systems by using fuzzy rule based systems instead of traditional expert systems. Thus all the various ways of integration are available for fuzzy connectionist systems. Additio

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Genetic Algorithms and Neural Networks,ndividually. In the early 1990’s, the revolution in the research and application of neural networks was followed by a surge in activity for genetic algorithms. By 1994, several conferences and publications had been dedicated to genetic algorithms where they had formerly been an adjunct of neural net

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Genetic Algorithms and Fuzzy Systems,neural networks. The pioneering work in this area starts around 1989 and much of the initiative is due to Charles Karr. The most promising application area for the short term is the use of genetic algorithms to improve fuzzy logic controllers. This is an emerging field in which important work has pr

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Genetic Algorithms and Expert Systems,oblems are impossible or at least difficult to address with these technologies. For example, applications involving scheduling and resource planning continue to be challenging subjects of research and development. Generic methods are sought that can be applied easily to practical problems. Genetic a