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    IJCAI
    1989
    110views Artificial Intelligence» more  IJCAI 1989»
    Training Feedforward Neural Networks Using Genetic Algorithms
    13 years 8 months ago
    Training Feedforward Neural Networks Using Genetic Algorithms
    Download  dli.iiit.ac.in
    Multilayered feedforward neural networks possess a number of properties which make them particularly suited to complex pattern classification problems. However, their application ...
    David J. Montana, Lawrence Davis
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    ESANN
    2003
    132views Neural Networks» more  ESANN 2003»
    Extraction of fuzzy rules from trained neural network using evolutionary algorithm
    13 years 8 months ago
    Extraction of fuzzy rules from trained neural network using evolutionary algorithm
    Download  www.dice.ucl.ac.be
    This paper presents our approach to the rule extraction problem from trained neural network. A method called REX is briefly described. REX acquires a set of fuzzy rules using an ev...
    Urszula Markowska-Kaczmar, Wojciech Trelak
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    IJIT
    2004
    306views Artificial Intelligence» more  IJIT 2004»
    A Comparison of First and Second Order Training Algorithms for Artificial Neural Networks
    13 years 8 months ago
    A Comparison of First and Second Order Training Algorithms for Artificial Neural Networks
    Download  www.waset.org
    Minimization methods for training feed-forward networks with Backpropagation are compared. Feedforward network training is a special case of functional minimization, where no expli...
    Syed Muhammad Aqil Burney, Tahseen Ahmed Jilani, C...
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    IJCAI
    1997
    158views Artificial Intelligence» more  IJCAI 1997»
    Extracting Propositions from Trained Neural Networks
    13 years 8 months ago
    Extracting Propositions from Trained Neural Networks
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    This paper presents an algorithm for extract­ ing propositions from trained neural networks. The algorithm is a decompositional approach which can be applied to any neural networ...
    Hiroshi Tsukimoto
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    ICMCS
    2006
    IEEE
    115views Multimedia» more  ICMCS 2006»
    On Training Neural Network Algorithms for Odor Identification for Future Multimedia Communication Systems
    14 years 1 months ago
    On Training Neural Network Algorithms for Odor Identification for Future Multimedia Communication Systems
    Download  www.cecs.uci.edu
    Future multimedia communication system can be developed to identify, transmit and provide odors besides voice and image. In this paper, an improved odor identification method is i...
    Ki-Hyeon Kwon, Namyong Kim, Hyung-Gi Byun, Krishna...
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