| 基于自由搜索的LS-SVM在墒情预测中的应用 |
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| 引用本文： | 张展羽,陈子平,王斌,李新虎.基于自由搜索的LS-SVM在墒情预测中的应用[J].系统工程理论与实践,2010,30(2):201-206. |
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| 作者姓名： | 张展羽 陈子平 王斌 李新虎 |
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| 作者单位： | 1. 河海大学,南方地区高效灌排与农业水土环境教育部重点实验室,南京210098;河海大学,水利水电学院,南京,210098
2. 东北农业大学水利与建筑学院,哈尔滨,150030 |
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| 摘 要： | 为有效地利用墒情监测资料预测未来墒情,考虑支持向量机的结构风险最小化准则和自由搜索算法良好的全局优化特点,应用最小二乘支持向量机方法,构造了优化目标函数,引入自由搜索算法对该目标函数寻优从而辨识模型参数,建立了预测墒情的最小二乘支持向量机(LS-SVM)模型.实例分析表明,支持向量机方法对墒情序列的平稳性要求不高,且模型易于实现,与传统的时间序列模型以及基于粒子群算法和鱼群算法的LS-SVM模型相比,基于自由搜索算法的LS-SVM模型具有较好的模拟及预测精度,相对误差小于15%的模拟值及预测值分别达到了100%和94.4%.
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| 关 键 词： | 时间序列分析 支持向量机 自由搜索 粒子群算法 鱼群算法 |
Soil moisture content series prediction based on LS-SVM within free search |
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| ZHANG Zhan-yu,CHEN Zi-ping,WANG Bin,LI Xin-hu.Soil moisture content series prediction based on LS-SVM within free search[J].Systems Engineering —Theory & Practice,2010,30(2):201-206. |
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| Authors: | ZHANG Zhan-yu CHEN Zi-ping WANG Bin LI Xin-hu |
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| Institution: | ZHANG Zhan-yu~(1,2),CHEN Zi-ping~(1,WANG Bin~3,LI Xin-hu~(1,2) (1.Key Laboratory of Efficient Irrigation-Drainage , Agricultural Soil-Water Environment in Southern China,Ministry of Education,Hohai University,Nanjing 210098,China,2.College of Water Conservancy , Hydropower Engineering,3.College of Water Conservancy , Building Engineering,Northeast Agricultural University,Harbin 150030,China) |
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| Abstract: | Based on the structure risk minimum criterion of support vector machine(SVM) and the global optimization characteristic of free search algorithm(FS),the least square-SVM(LS-SVM) is applied to establish the model for predicting the soil moisture content,and FS is used to optimize the parameters of the model.The application shows that the model is better than the models based on particle swarm optimization(PSO),fish swarm algorithm(FSA) and time series analysis(TSA) method,it possesses the advantage of high a... |
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| Keywords: | time series analysis support vector machines free search particle swarm optimization fish swarm algorithm |
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