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[其他资源] A Genetic Programming-Driven Data Fitting Method

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杨利霞        

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    2021-8-11 17:59
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    发表于 2020-11-12 16:33 |只看该作者 |正序浏览
    |招呼Ta 关注Ta
    A Genetic Programming-Driven
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    Data Fitting Method
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    Data fifitting is the process of constructing a curve, or a set of mathematical functions, that has& H' z- Y, a1 Q8 W
    the best fifit to a series of data points. Different with constructing a fifitting model from same type of function,
    . G" v1 t: O2 L, Dsuch as the polynomial model, we notice that a hybrid fifitting model with multiple types of function may have% t1 {. S3 q; B( s) g1 F7 g0 m. u
    a better fifitting result. Moreover, this also shows better interpretability. However, a perfect smooth hybrid
    * E% y0 Y) M/ a- ~/ M6 hfifitting model depends on a reasonable combination of multiple functions and a set of effective parameters.
    4 T3 G6 }; G4 C9 I/ |% k! n! k( P! sThat is a high-dimensional multi-objective optimization problem. This paper proposes a novel data fifitting
    ( k+ U3 S( T" t; S& Nmodel construction approach. In this approach, the model is expressed by an improved tree coding expression" ~, A) K4 z! p, X
    and constructed through an evolution search process driven by the genetic programming. In order to verify/ q; Z$ a, F! O
    the validity of generated hybrid fifitting model, 6 prediction problems are chosen for experiment studies. The
      j& f, y( e5 P4 j# n( aexperimental results show that the proposed method is superior to 7 typical methods in terms of the prediction( b+ O% G* b* {4 b
    accuracy and interpretability
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    & N5 ~% t4 R1 x8 W7 I
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    A Genetic Programming-Driven.pdf

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