مشاهده مشخصات مقاله
Adaptive Parameter Selection Scheme for PSO: A Learning Automata Approach
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نویسنده (ها) |
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Ali B. Hashemi
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M.R Meybodi
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مربوط به کنفرانس |
چهاردهمین کنفرانس بینالمللی سالانه انجمن کامپیوتر ایران |
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چکیده |
PSO, like many stochastic search methods, is very
sensitive to efficient parameter setting. As modifying a
single parameter may result in a large effect. In this
paper, we propose a new a new learning automatabased
approach for adaptive PSO parameter selection.
In this approach three learning automata are utilized
to determine values of each parameter for updating
particles velocity namely inertia weight, cognitive and
social components. Experimental results show that the
proposed algorithms compared to other schemes such
as SPSO, PSO-IW, PSO TVAC, PSO-LP, DAPSO,
GPSO, and DCPSO have the same or even higher
ability to find better local minima. In addition,
proposed algorithms converge to stopping criteria
significantly faster than most of the PSO algorithms. |
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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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