مشاهده مشخصات مقاله
Fast and Parsimonious Self-Organizing Fuzzy Neural Network
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Authors |
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Omid Khayat
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Javad Razjouyan
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Hadi ChahkandiNejad
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Mahdi Mohammad Abadi
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Mohammad Mehdi
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Conference |
چهاردهمین کنفرانس بینالمللی سالانه انجمن کامپیوتر ایران |
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Abstract |
This paper introduces a revisited hybrid algorithm for
function approximation. In this paper, a simple and fast
learning algorithm is proposed, which automates
structure and parameter identification simultaneously
based on input-target samples. First, without need of
clustering, the initial structure of the network with the
specified number of rules is established, and then a
training process based on the error of other training
samples is applied to obtain a more precision model.
After the network structure is identified, an optimization
learning, based on the criteria error, is performed to
optimize the obtained parameter set of the premise parts
and the consequent parts. At the end, comprehensive
comparisons are made with other approaches to
demonstrate that the proposed algorithm is superior in
term of compact structure, convergence speed, memory
usage and learning efficiency. |
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قیمت |
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برای اعضای سایت : 100,000 Rial
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برای دانشجویان عضو انجمن : 20,000 Rial
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برای اعضای عادی انجمن : 40,000 Rial
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خرید مقاله
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