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| 基于粒子群优化径向基神经网络的水质指标预测 | |
| 引用本文： | 操建华,林宏伟,张实诚.基于粒子群优化径向基神经网络的水质指标预测[J].煤炭技术,2010,29(2). |
| 作者姓名： | 操建华 林宏伟 张实诚 |
| 作者单位： | 1. 顺德职业技术学院电子工程系,广东,佛山,528300 2. 十堰职业技术学院环化系,湖北,十堰,442000 3. 湖北十堰市环境保护局,湖北,十堰,442000 |
| 摘 要： | 为掌握丹江口库区水质未来的变化趋势以及预防污染事件的发生,建立了一个水质指标的预测模型。利用库区某断面自动检测站的水质指标实测参数作为学习样本,选取化学需养量(COD)、生化需养量(BOD)、PH值、氨氮(NH3-N)、总磷(TP)、总氮(TN)等指标作为预测参数,运用粒子群算法优化RBF神经网络的预测模型,对丹江口库区水质指标进行预测,结果表明,利用基于粒子群优化径向基神经网络对水质指标预测具有较高的精度,相对误差小于7%,该模型具有良好的可行性和有效性。 |
| 关 键 词： | 粒子群 径向基函数 神经网络 水质 预测 丹江口水库 |
Prediction of water Quality Index in DanJiangkou Reserveior Based on BP Neural Network Model |
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| CAO Jian-hua,LIN Hong-wei,ZHANG Shi-cheng.Prediction of water Quality Index in DanJiangkou Reserveior Based on BP Neural Network Model[J].Coal Technology,2010,29(2). | |
| Authors: | CAO Jian-hua LIN Hong-wei ZHANG Shi-cheng |
| Affiliation: | 1.Department of Electronic engineering/a>;Shunde Ploytechnic/a>;Fuoshan 528300/a>;China/a>;2.Department of Environment & Chemistry/a>;Shiyan 442000/a>;3.Environment Protection Bureau/a>;China |
| Abstract: | A predictive model was set up to grasp the future change tendency of water quality about Danjiangkou reservoir and prevent further pollution.The historical time series of water quality indexes in district border of Danjiangkou reservoir were taken as instructive samples,and six indexes were taken as predicted indexes,such as chemical oxygen demand(COD),total phosphor(TP),total nitrogen(TN).The samples were modeled and optimized with RBF neural network based on Particle Swarm Optimization(PSO).The predicted ... |
| Keywords: | PSO RBF neural network water quality index prediction danjiangkou reservoir |
| 本文献已被 CNKI 万方数据 等数据库收录！ | |