Some Improvements of Genetic Programming in Data Fitting

Hu Jie; Jia Quan Feng; Da Lin Chen

doi:10.4028/www.scientific.net/AMR.201-203.2536

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 201-203Some Improvements of Genetic Programming in Data...

Some Improvements of Genetic Programming in Data Fitting

Abstract:

This paper proposed some improvement measures of Genetic Programming (GP) in data fitting, including developed new ways of crossover and mutation, improved the calculation efficiency greatly, and avoided the problem of parse tree expansion. The new adopted mutation method improved the problem of constant modification to some extent. Numerical simulation obtained a considerable good fitting and prediction precision.

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Advanced Manufacturing Systems, ICMSE 2011

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Periodical:

Advanced Materials Research (Volumes 201-203)

Pages:

2536-2539

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.201-203.2536

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Online since:

February 2011

Authors:

Hu Jie, Jia Quan Feng, Da Lin Chen

Keywords:

Data Fitting, Genetic Algorithm (GA), Genetic Programming, Prediction

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