مشاهده مشخصات مقاله
A New Evolutionary Algorithm for Structure Learning in Bayesian Networks
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نویسنده (ها) |
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A. R. Khanteymoori
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M. B. Menhaj
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M. M. Homayounpour
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مربوط به کنفرانس |
چهاردهمین کنفرانس بینالمللی سالانه انجمن کامپیوتر ایران |
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چکیده |
A new structure learning approach for Bayesian
networks (BNs) based on asexual reproduction
optimization (ARO) is proposed in this paper. ARO can
be essentially considered as an evolutionary based
algorithm that mathematically models the budding
mechanism of asexual reproduction. In ARO, a parent
produces a bud through a reproduction operator;
thereafter the parent and its bud compete to survive
according to a performance index obtained from the
underlying objective function of the optimization
problem; this leads to the fitter individual. The
proposed method is applied to real-world and
benchmark applications, while its effectiveness is
demonstrated through computer simulation. Results of
simulation show that ARO outperforms GA because
ARO results good structure in comparison with GA
and the speed of convergence in ARO is more than GA.
Finally, the ARO performance is statistically shown. |
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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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