مشاهده مشخصات مقاله
Polynomial Kernel Function and its Application in Locally Polynomial Neurofuzzy Models
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نویسنده (ها) |
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A. Shirvani
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H. Chegini
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S. Setayeshi
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C. Lucas
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مربوط به کنفرانس |
چهاردهمین کنفرانس بینالمللی سالانه انجمن کامپیوتر ایران |
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چکیده |
Polynomials are one of the most powerful functions
that have been used in many fields of mathematics
such as curve fitting and regression. Low order
polynomials are desired for their smoothness1, good
local approximation and interpolation. Being smooth,
they can be used to locally approximate almost any
derivable function. This means that when linear
functions fail in approximation (e.g. where the first
order Taylor expansion equals zero) polynomial
functions can be used in local approximation, such
that one can achieve better estimations at extremums.
In this paper, application of polynomial kernel
functions in locally linear neurofuzzy models is shown.
Using polynomial kernels in local models, better local
approximations in prediction of chaotic time series
such as Mackey-Glass is achieved, and the capability
of the neurofuzzy network is enhanced. |
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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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