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Titlebook: Computational Intelligence Paradigms; Innovative Applicati Lakhmi C. Jain,Mika Sato-Ilic,Canicious Abeynayake Book 2008 Springer-Verlag Ber

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發(fā)表于 2025-3-21 18:28:31 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Computational Intelligence Paradigms
副標題Innovative Applicati
編輯Lakhmi C. Jain,Mika Sato-Ilic,Canicious Abeynayake
視頻videohttp://file.papertrans.cn/233/232399/232399.mp4
概述Presents innovative applications of advanced computational intelligence paradigms
叢書名稱Studies in Computational Intelligence
圖書封面Titlebook: Computational Intelligence Paradigms; Innovative Applicati Lakhmi C. Jain,Mika Sato-Ilic,Canicious Abeynayake Book 2008 Springer-Verlag Ber
描述.System designers are faced with a large set of data which has to be analysed and processed efficiently. Advanced computational intelligence paradigms present tremendous advantages by offering capabilities such as learning, generalisation and robustness. These capabilities help in designing complex systems which are intelligent and robust....The book includes a sample of research on the innovative applications of advanced computational intelligence paradigms. The characteristics of computational intelligence paradigms such as learning, generalization based on learned knowledge, knowledge extraction from imprecise and incomplete data are the extremely important for the implementation of intelligent machines. The chapters include architectures of computational intelligence paradigms, knowledge discovery, pattern classification, clusters, support vector machines and gene linkage analysis. We believe that the research on computational intelligence will simulate great interest among designers and researchers of complex systems. It is important to use the fusion of various constituents of computational intelligence to offset the demerits of one paradigm by the merits of another..
出版日期Book 2008
關鍵詞algorithm; algorithms; architecture; calculus; classification; cluster analysis; complex systems; computati
版次1
doihttps://doi.org/10.1007/978-3-540-79474-5
isbn_softcover978-3-642-09839-0
isbn_ebook978-3-540-79474-5Series ISSN 1860-949X Series E-ISSN 1860-9503
issn_series 1860-949X
copyrightSpringer-Verlag Berlin Heidelberg 2008
The information of publication is updating

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沙發(fā)
發(fā)表于 2025-3-21 22:43:40 | 只看該作者
Studies in Computational Intelligencehttp://image.papertrans.cn/c/image/232399.jpg
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https://doi.org/10.1007/978-3-540-79474-5algorithm; algorithms; architecture; calculus; classification; cluster analysis; complex systems; computati
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Thinking About Urban Materialityl concept of this new, innovative computing field. The main constituents of CI, which include artificial neural networks, fuzzy systems, and evolutionary algorithms, are explained. In addition, different hybrid CI models arisen from synergy of neural, fuzzy, and evolutionary computational paradigms
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發(fā)表于 2025-3-22 16:38:28 | 只看該作者
Thinking About Urban Materialityn efficient manner) and interpretable (so that the results are easily understood by the user or designer). The logic is the language of interpretable constructs. Neural architectures offer a flexible and convenient setting for learning. The study conveys a message that a suitable combination of logi
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https://doi.org/10.1007/978-981-15-4650-1lled MembershipMap, strives to granulate and extract the underlying sub-concepts of each raw attribute. The orthogonal union of these sub-concepts are then used to define a new membership space. The sub-concept soft labels of each point in the original space determine the position of that point in t
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Thinking About Urban Materialityrn classifier. Since then, many studies have explored different issues concerning FAM optimization, training and evaluation, e.g., model sensitivity to parameters, ordering strategy for the presentation of the training patterns, training method and method of predicting the classification accuracy. O
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Sensing Place: Living with Melbourne’s Stoneclassification in a multivariate setting, i.e. such that complex, non-scalar predictions must be produced in correspondence to input vectors. Examples of these tasks range from natural language parsing to speech recognition, machine translation, image segmentation, handwritten character recognition
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