[PDF.50hb] Adaptive Differential Evolution: A Robust Approach to Multimodal Problem Optimization (Adaptation, Learning, and Optimization)

Adaptive Differential Evolution: A Robust Approach to Multimodal Problem Optimization (Adaptation, Learning, and Optimization)

[PDF.ed23] Adaptive Differential Evolution: A Robust Approach to Multimodal Problem Optimization (Adaptation, Learning, and Optimization)

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 | #4891181 in Books |  Springer |  2009-09-02 | Original language:English | PDF # 1 |  9.21 x.44 x6.14l,.95 | File type: PDF | 164 pages

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||0 of 0 people found the following review helpful.| good references|By G. Orr|Generally I would give this book high marks for its overview of algorithms (though it is not exhaustive), and its description of the JADE algorithm. The nomenclature could be clearer, and the figures are almost impossible to read. One needs a magnifying glass to see some of the captions. These figures were probably photocopied from the autor's thesis,|From the Back Cover||Optimization problems are ubiquitous in academic research and real-world applications wherever such resources as space, time and cost are limited. Researchers and practitioners need to solve problems fundamental to their daily work which, ho

The fundamental theme of this book is theoretical study of differential evolution and algorithmic analysis of parameter adaptive schemes. The book offers real-world insights into a variety of large-scale complex industrial applications.

You easily download any file type for your device.Adaptive Differential Evolution: A Robust Approach to Multimodal Problem Optimization (Adaptation, Learning, and Optimization)   |  Jingqiao Zhang, Arthur C. Sanderson. A good, fresh read, highly recommended.

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