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Titlebook: Advanced Intelligent Computing Theories and Applications; With Aspects of Cont De-Shuang Huang,Laurent Heutte,Marco Loog Conference proceed

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Recommending Expert System of Project Reviewing Based on CBR978-1-4302-3408-1
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https://doi.org/10.1007/978-3-030-17929-8urons, which is also called network structure learning problem. In order to solve the above problem and to improve the generalization performance of fuzzy RBF network, a kind of constructive T-S fuzzy normalized RBF network was proposed by combining T-S fuzzy model with normalized RBF network. The m
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BiCMOS Technology and ApplicationsARM is a self organizing architecture. Dynamically adjusting the size of sensitivity regions of each neuron and adaptively pruning one of the redundant neurons, the ARM can preserve resources (available neurons) to accommodate more categories. The Q-learning is a dynamic programming-based reinforcem
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A Perspective On BiCMOS Trends,y adopting the method of decomposing the state space to sub-regions and by using the technique of matrix norm, some delay-independent stability algebraic criteria are obtained, and the attractive domains are estimated. The results obtained in this paper need only to compute the norm of some matrices
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A Perspective On BiCMOS Trends,ined input variable and similar day selection technique is proposed. Among so many load influential factors, rough set theory is used to select most relevant ones in order to make the input neurons representative. Next, Euclidean norm based similar day selection is used both for the forecasting day
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R. Lahri,S. P. Joshi,B. Bastaniwidely used model neurons in the neuroscience society, the bursting Hindmarsh-Rose neurons. For an input pattern which is an overlapped superposition of several stored patterns, it is shown that the proposed neuronal network model is capable of segmenting out each pattern one after another as synchr
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R. Lahri,S. P. Joshi,B. Bastanieal the ’black-box’. From this point, the comprehensibility of the rules extracted is very important. If not so, rule extraction is unmeaning. For problems with continuous-valued and discrete-valued attributes, there are few existing algorithms to process. This paper presents two ideas to resolve th
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