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| 变权组合模型在景观水体水质模拟中的应用 | |
| 引用本文： | 赵加斌, 赵新华, 彭森. 变权组合模型在景观水体水质模拟中的应用[J]. 环境工程学报, 2015, 9(9): 4206-4210. doi: 10.12030/j.cjee.20150918 |
| 作者姓名： | 赵加斌 赵新华 彭森 |
| 作者单位： | 1.天津大学环境科学与工程学院, 天津 300072 |
| 基金项目： | 国家水体污染控制与治理科技重大专项(2014ZX07203-009) 国家自然科学基金资助项目(51308385) |
| 摘 要： | 针对景观水体的水质模拟与预测问题,在BP神经网络和支持向量机模型的基础上,建立了权重随输入量变化的变权组合模型。该模型既能充分利用各个单一模型的优点,又能避免固定权重分配的弊端。经实例验证,与单一的BP神经网络和支持向量机模型相比,变权组合模型拟合精度更高,预测结果更为准确。 |
| 关 键 词： | 景观水体 水质模拟 BP神经网络 支持向量机 变权组合 |
| 收稿时间： | 2014-08-22 |
Application of combination model of variable weight in landscape water quality simulation |
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| Zhao Jiabin, Zhao Xinhua, Peng Sen. Application of combination model of variable weight in landscape water quality simulation[J]. Chinese Journal of Environmental Engineering, 2015, 9(9): 4206-4210. doi: 10.12030/j.cjee.20150918 | |
| Authors: | Zhao Jiabin Zhao Xinhua Peng Sen |
| Affiliation: | 1.School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China |
| Abstract: | In order to simulate and predict landscape water quality, we proposed a combination model of variable weight, which based on the back-propagation (BP) neural network model and support vector machine model. The combination model of variable weight could make full use of the single model, and it would avoid the drawbacks of the fixed weight distribution. With the case study and comparison of the BP neural network model and support vector machine mode, we could find that the combination model of variable weight is much better in fitting accuracy and prediction results. |
| Keywords: | landscape water water quality simulation BP neural network support vector machine combination model of variable weight |
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