Titlebook: Computational Intelligence; A Methodological Int Rudolf Kruse,Christian Borgelt,Pascal Held Textbook 20131st edition Springer-Verlag London

Exaltation

書目名稱Computational Intelligence影響因子(影響力)




書目名稱Computational Intelligence影響因子(影響力)學(xué)科排名




書目名稱Computational Intelligence網(wǎng)絡(luò)公開度




書目名稱Computational Intelligence網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Computational Intelligence被引頻次




書目名稱Computational Intelligence被引頻次學(xué)科排名




書目名稱Computational Intelligence年度引用




書目名稱Computational Intelligence年度引用學(xué)科排名




書目名稱Computational Intelligence讀者反饋




書目名稱Computational Intelligence讀者反饋學(xué)科排名

anagen

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Introduction They consist of a large number of fairly simple units, the so-called ., which are working in parallel. These neurons communicate by sending information in the form of activation signals, along directed connections, to each other. A commonly used synonym for “neural network” is the term “connectioni

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induct

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Radial Basis Function Networksf layers is always three, that is, there is exactly one hidden layer. In addition, radial basis function networks differ from multi-layer perceptrons in the network input and activation functions, especially in the hidden layer. In this hidden layer . are employed, which are responsible for the name

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Self-organizing Mapsidden layer of a radial basis function network is already the output layer of a self-organizing map. This output layer also has an internal structure, since the neurons are arranged in a grid. The neighborhood relationships resulting from this grid are exploited in the training process in order to d

仲裁者

Hopfield Networksever, we turn to so-called ., that is, networks, the graph of which may contain (directed) cycles. We start with one of the simplest forms, the so-called ., which originated as physical models to describe magnetism. Hopfield networks are indeed closely related to the Ising model of magnetism.

Ingrained

Peak-Bone-Mass

Introduction to Evolutionary Algorithmshich also includes, for example, particle swarm and ant colony optimization, which are inspired by other biological structures and processes, as well as classical methods like simulated annealing, which is inspired by a thermodynamical process. The core principle of evolutionary algorithms is to app