Forest Fire Disaster Area Prediction Based on Genetic Algorithm and Support Vector Machine
2012 ◽
Vol 446-449
◽
pp. 3037-3041
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Keyword(s):
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.
2012 ◽
Vol 446-449
◽
pp. 3037-3041
Keyword(s):
2014 ◽
Vol 587-589
◽
pp. 2100-2104
Keyword(s):
Keyword(s):
2019 ◽
Vol 259
◽
pp. 02007
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2011 ◽
Vol 201-203
◽
pp. 2277-2280
Mapping Mineral Prospectivity Using a Hybrid Genetic Algorithm–Support Vector Machine (GA–SVM) Model
2021 ◽
Vol 10
(11)
◽
pp. 766
2018 ◽
Vol 1
(1)
◽
pp. 120-130
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