| 基于LS-SVR、BP-ANN和MLR模型的PM10浓度预测 |
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| 引用本文： | 冯晓秀,高志文,李风军,虎雪娇.基于LS-SVR、BP-ANN和MLR模型的PM10浓度预测[J].中国环境监测,2014,30(6):138-141. |
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| 作者姓名： | 冯晓秀 高志文 李风军 虎雪娇 |
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| 作者单位： | 宁夏大学数学计算机学院, 宁夏 银川 750021;宁夏大学数学计算机学院, 宁夏 银川 750021;宁夏大学数学计算机学院, 宁夏 银川 750021;西安建筑科技大学环境与市政工程学院, 陕西 西安 710055 |
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| 基金项目： | 国家自然科学基金资助项目(61063020,11261042) |
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| 摘 要： | 利用宁东能源化工基地PM10和气象监测数据,分别采用LS-SVR、BP-ANN和传统MLR模型预测PM10浓度变化。结果表明,较BP-ANN模型、MLR模型,LS-SVR模型能更好地刻画PM10浓度与各气象因素间的非线性相依关系,更准确地预测PM10浓度。
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| 关 键 词： | LS-SVR BP-ANN MLR PM10 预测 |
| 收稿时间： | 2013/11/20 0:00:00 |
| 修稿时间： | 2014/4/14 0:00:00 |
Prediction of PM10 Concentrations Based on LS-SVR, BP-ANN and MLR Models |
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| FENG Xiao-xiu,GAO Zhi-wen,LI Feng-jun and HU Xue-jiao.Prediction of PM10 Concentrations Based on LS-SVR, BP-ANN and MLR Models[J].Environmental Monitoring in China,2014,30(6):138-141. |
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| Authors: | FENG Xiao-xiu GAO Zhi-wen LI Feng-jun and HU Xue-jiao |
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| Institution: | School of Mathematics and Computer Science, Ningxia University, Yinchuan 750021, China;School of Mathematics and Computer Science, Ningxia University, Yinchuan 750021, China;School of Mathematics and Computer Science, Ningxia University, Yinchuan 750021, China;College of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China |
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| Abstract: | Using ambient PM10 concentrations and meteorological data of Ningdong Energy and Chemistry Industry Base, predicted PM10 concentrations variation based on LS-SVR, BP-ANN and traditional MLR models, respectively. It was shown that the LS-SVR model could better depict the nonlinear dependency relationship between PM10 concentrations and meteorological factors, more accurately predict PM10 concentrations, comparing to BP-ANN and MLR. |
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| Keywords: | LS-SVR BP-ANN MLR PM10 prediction |
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