Titlebook: Real World Applications of Computational Intelligence; Mircea Negoita,Bernd Reusch Book 2005 Springer-Verlag Berlin Heidelberg 2005 algori

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Data Driven Fuzzy Modelling with Neural Networks,nd of fuzzy rules with support of neural networks. Finally it is shown that it is possible to extract compensating fuzzy if-then rules from a great number of already existing feedforward neural networks.

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Supporting Deep Learning in an Open-ended Domain,r self-explanation can be used in an open-ended, ill-structured domain. For this purpose, we enhanced KERMIT, an intelligent tutoring system that teaches conceptual database design. The resulting system, KERMIT-SE, supports self-explanation by engaging students in tutorial dialogues when their solut

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Data Driven Fuzzy Modelling with Neural Networks,es where the premises are not connected by .-norms, but by a compensating aggregation operator are discussed. A method is presented to extract this kind of fuzzy rules with support of neural networks. Finally it is shown that it is possible to extract compensating fuzzy if-then rules from a great nu

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Hybrid Computational Intelligence Systems for Real World Applications,real-world applications which make use of computational intelligence. The introduction describes fuzzy logic and evolutionary algorithms in detail, whereas the artificial neural networks are only described briefly. For a more detailed introduction see the chapter of Moraga in this book. The applicat

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Bioinformatics with Evolutionary Computation,inition of the problem, than it is to apply our powerful algorithms in an attempt to solve it. Even with evolutionary computation, a serious attempt at specifying a definition of the problem must come first (the homework), before any attempt to apply the computational intelligence algorithm. This is

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Maximization of Combustion Efficiency: A Data Mining Approach,ation on boiler efficiency is investigated. The study showed that the data transformed with wavelet algorithms (Haar and Daubechies) provided better cross-validation accuracy, while moving average and wavelets resulted in similar prediction accuracy. The relationship between the length of the contro