مشاهده مشخصات مقاله
Accuracy-based Classifier Systems Using Evolutionary Neural Networks Representation
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نویسنده (ها) |
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M. Sabeti
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P. Zahadat
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S. D. Katebi
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مربوط به کنفرانس |
دوازدهمین کنفرانس بینالمللی سالانه انجمن کامپیوتر ایران |
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چکیده |
Accuracy-based classifier systems (XCS) traditionally use a binary string rule representation with wildcards
added to allow for generalization over the population encoding. However, the simple scheme has some of
drawbacks in complex problems. A neural network-based representation is used to aid their use in complex
problem. Here each rule's condition and action are represented by a small network evolved through the action of
the genetic algorithm. Also in this work a second neural network is used as classifier's prediction, trained by
back propagation. After describing the changes required to the standard XCS functionality, the results are
presented using neural network to represent individual rules. Examples of use are given to illustrate the
effectiveness of the proposed approached. |
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قیمت |
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برای اعضای سایت : ۱٠٠,٠٠٠ ریال
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برای دانشجویان عضو انجمن : ۲٠,٠٠٠ ریال
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برای اعضای عادی انجمن : ۴٠,٠٠٠ ریال
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خرید مقاله
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