| 基于GA-SVM的渤海湾富营养化模型 |
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| 引用本文： | 向先全,陶建华. 基于GA-SVM的渤海湾富营养化模型[J]. 天津大学学报(自然科学与工程技术版), 2011, 44(3) |
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| 作者姓名： | 向先全 陶建华 |
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| 作者单位： | 天津大学环境科学与工程学院;天津大学机械工程学院; |
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| 基金项目： | 国家自然科学基金资助项目(10872144) |
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| 摘 要： | 为了更好地模拟和认知渤海湾富营养化的复杂行为,通过研究遗传算法(GA)和支持向量机(SVM)的结合形式,即参数寻优和特征选择,以渤海湾水质实测资料为依据,叶绿素a的质量浓度为输出,建立了GA-SVM的富营养化模型.无特征选择时,用遗传算法对支持向量机的参数(惩罚参数和核参数)进行自适应地优选,预测模型的均方误差可达到1.831μg/L,具有较好的认知、泛化能力.再利用遗传算法二进制编码及启发式寻优的优点,对所建模型的输入空间进行特征选择,提取出代表性的特征变量:DO%、pH值、水温、COD、盐度以及氨氮.特征提取后预测模型的均方误差可达到1.363μg/L,模型性能有了很大提高.分析表明,COD、盐度及氨氮可作为人为控制的首要指标.
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| 关 键 词： | 富营养化模型 支持向量机 遗传算法 参数寻优 特征选择 渤海湾 |
Eutrophication Model of Bohai Bay Based on GA-SVM |
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| XIANG Xian-quan,TAO Jian-hua. Eutrophication Model of Bohai Bay Based on GA-SVM[J]. Journal of Tianjin University(Science and Technology), 2011, 44(3) |
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| Authors: | XIANG Xian-quan TAO Jian-hua |
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| Affiliation: | XIANG Xian-quan1,TAO Jian-hua2(1.School of Environmental Science and Engineering,Tianjin University,Tianjin 300072,China,2.School of Mechanical Engineering,China) |
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| Abstract: | For better simulating and cognizing the complex eutrophication behaviors of Bohai Bay,the combining forms of genetic algorithm and support vector machine(parameter optimization and feature selection) have been re-searched to establish GA-SVM eutrophication model for Bohai Bay based on the field measured data,and chloro-phyll_a content has been selected as the model output.Firstly,with GA self-adaptive optimizing for penalty parameter and kernel parameter,the root mean square error(RMSE) of SVM test model wa... |
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| Keywords: | eutrophication model support vector machine genetic algorithm parameters optimization feature selection Bohai Bay |
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