مشاهده مشخصات مقاله
Evolution of Neural Network Architecture and Weights Using Mutation Based Genetic Algorithm
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نویسنده (ها) |
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A. Nadi
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S. S. Tayarani-Bathaie
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R. Safabakhsh
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مربوط به کنفرانس |
چهاردهمین کنفرانس بینالمللی سالانه انجمن کامپیوتر ایران |
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چکیده |
In this paper we present a new approach for
evolving an optimized neural network architecture for a
three layer feedforward neural network with a mutation
based genetic algorithm. In this study we will optimize the
weights and the network architecture simultaneously
through a new presentation for the three layer feedforward
neural network. The goal of the method is to find the
optimal number of neurons and their appropriate weights.
This optimization problem so far has been solved by looking
at the general architecture of the network but we optimize
the individual neurons of the hidden layer. This change
results in a search space with much higher resolution and an
increased speed of convergence. Evaluation of algorithm by
3 data sets reveals that this method shows a very good
performance in comparison to current methods. |
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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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