沈阳农业大学学报2013，Vol.44Issue(2)：190-194,5.DOI:10.3969/j.issn.1000-1700.2013.02.011
基于遗传算法优化的支持向量机干旱预测模型
Drought Prediction Model Based on Genetic Algorithm Optimization Support Vector Machine (SVM)
摘要
Abstract
In order to overcome the defects on the artificial choice blindness for support vector machine parameters and dependence on the experience,we used genetic algorithm to optimize the support vector machine C,g parameters,realizing the optimization of the parameters of support vector machine,reducing the workload of parameter choice and improving the prediction precision.Genetic algorithm support vector machine model was applied to the flood drought prediction of Hun River Basin,through the MATLAB programming to build the model.In Haicheng,Dawa,Liaoyang and Shenyang,the rainfall prediction model was built.The model predictive value and real value was well fitted,the prediction precision met the requirements.So the model for flood drought of Hun River basin prediction is feasible,useful for decision-making department,deployment of drought fighting work and reasonable utilization and allocation of water resources.关键词
遗传算法/支持向量机/干旱预测/降雨量Key words
genetic algorithm / support vector machine /droughts prediction /rainfall.分类
天文与地球科学引用本文复制引用
迟道才,张兰芬,李雪,王堃,吴秀明,张特男..基于遗传算法优化的支持向量机干旱预测模型[J].沈阳农业大学学报,2013,44(2):190-194,5.基金项目
高等学校博士学科点专项科研基金联合资助项目(201112103110007) （201112103110007）
沈阳市科技局农业科技攻关项目(F12-129-3-00) （F12-129-3-00）
