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Titlebook: Computational Intelligence and Bioinspired Systems; 8th International Wo Joan Cabestany,Alberto Prieto,Francisco Sandoval Conference procee

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书目名称Computational Intelligence and Bioinspired Systems
副标题8th International Wo
编辑Joan Cabestany,Alberto Prieto,Francisco Sandoval
视频video
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Computational Intelligence and Bioinspired Systems; 8th International Wo Joan Cabestany,Alberto Prieto,Francisco Sandoval Conference procee
描述We present in this volume the collection of finally accepted papers of the eighth edition of the “IWANN” conference (“International Work-Conference on Artificial Neural Networks”). This biennial meeting focuses on the foundations, theory, models and applications of systems inspired by nature (neural networks, fuzzy logic and evolutionary systems). Since the first edition of IWANN in Granada (LNCS 540, 1991), the Artificial Neural Network (ANN) community, and the domain itself, have matured and evolved. Under the ANN banner we find a very heterogeneous scenario with a main interest and objective: to better understand nature and beings for the correct elaboration of theories, models and new algorithms. For scientists, engineers and professionals working in the area, this is a very good way to get solid and competitive applications. We are facing a real revolution with the emergence of embedded intelligence in many artificial systems (systems covering diverse fields: industry, domotics, leisure, healthcare, … ). So we are convinced that an enormous amount of work must be, and should be, still done. Many pieces of the puzzle must be built and placed into their proper positions, offerin
出版日期Conference proceedings 2005
关键词Support Vector Machine; artificial neural network; cognition; computational intelligence; evolution; evol
版次1
doihttps://doi.org/10.1007/b136983
isbn_softcover978-3-540-26208-4
isbn_ebook978-3-540-32106-4Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2005
The information of publication is updating

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Memetic Algorithms to Product-Unit Neural Networks for Regression, the optimization algorithm is only applied at specific stages of the evolutionary process. The key aspect of our work is the use of a clustering algorithm to select the individuals to be optimized. The underlying idea is that we can achieve a very good performance if, instead of optimizing many ve
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