Titlebook: Genetic Algorithms; Concepts and Designs K. F. Man,K. S. Tang,S. Kwong Textbook 1999 Springer-Verlag London 1999 Text.algorithms.developmen

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書目名稱Genetic Algorithms影響因子(影響力)




書目名稱Genetic Algorithms影響因子(影響力)學(xué)科排名




書目名稱Genetic Algorithms網(wǎng)絡(luò)公開度




書目名稱Genetic Algorithms網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Genetic Algorithms被引頻次




書目名稱Genetic Algorithms被引頻次學(xué)科排名




書目名稱Genetic Algorithms年度引用




書目名稱Genetic Algorithms年度引用學(xué)科排名




書目名稱Genetic Algorithms讀者反饋




書目名稱Genetic Algorithms讀者反饋學(xué)科排名

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過時

Intrinsic Characteristics,esults obtained are quite good and are considered to be compatible to those derived from other techniques. However, a simply GA has difficulty in tackling complicated, multi-tasking and conflicting problems, and the speed of computation is generally regarded as slow. To enhance the capability of GA

產(chǎn)生

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Genetic Algorithms in Filtering, the computational power is ensured. In the case of real time processing, this requirement is necessary and obvious. Achieving this goal is by no means easy. This can be very involved in circumstances where the performance criteria are discrete, complex, multiobjective and very often, nonlinear.

Projection

Projection

Hierarchical Genetic Algorithms in Computational Intelligence,ligence (CI). This trend of development is understandable since computing power has become so much faster and cheaper nowadays, such that a required solution can be automatically obtained even when this is based upon a computationally intensive scheme.

CHECK

Genetic Algorithms in Speech Recognition Systems,ot only enhances the speed of recognition tremendously, but also improves the quality of the overall performance in recognizing the speech utterance. In general, there are two classic approaches for this development, namely, Dynamic Time Warping (DTW) and the Hidden Markov Model (HMM).

Deject

Genetic Algorithms in Communication Systems, These issues involve nonlinear and discrete functions for optimization which may not yield the adequate solutions easily using the classical gradient type of searching tools. The problem can be more severe when multiobjective functions are encountered.

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