Forest Fire Disaster Area Prediction Based on Genetic Algorithm and Support Vector Machine

Fang Xiao

doi:10.4028/www.scientific.net/AMR.446-449.3037

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 446-449Forest Fire Disaster Area Prediction Based on...

Forest Fire Disaster Area Prediction Based on Genetic Algorithm and Support Vector Machine

Abstract:

Forest fire disaster area prediction based on genetic algorithm and support vector machine is presented in the paper.Genetic algorithm is used to select appropriate parameters of support vector machine. Genetic algorithm can obtain the optimal solution by a series of iterative computations.The forest fire disaster area data in Jiangxi Province from 1970 to 1997 are used as our research data. The comparison of the forest fire disaster area forecasting results between the proposed GA-SVM model and the SVM model is given,which indicates that the proposed GA-SVM model has more excellent forest fire disaster area forecasting results than the SVM model.

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Periodical:

Advanced Materials Research (Volumes 446-449)

Pages:

3037-3041

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.446-449.3037

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Online since:

January 2012

Authors:

Fang Xiao

Keywords:

Forest Fire Disaster Area, Parameter Optimization, Support Vector Machine (SVM), Time Series

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