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| 应用改进BP神经网络进行用水量预测 | |
| 引用本文： | 麻凤海,杨维,杨帆,于晓曦.应用改进BP神经网络进行用水量预测[J].辽宁工程技术大学学报(自然科学版),2004,23(2):191-193. |
| 作者姓名： | 麻凤海 杨维 杨帆 于晓曦 |
| 作者单位： | 1. 辽宁工程技术大学,学科建设办公室,辽宁,阜新,123000 2. 本溪钢铁公司,辽宁,本溪,117100 3. 辽宁工程技术大学测量工程系,辽宁,阜新,123000 4. 辽宁工程技术大学土木建筑工程学院,辽宁,阜新,123000 |
| 基金项目： | 辽宁省教育厅攻关计划基金资助项目(202183392) |
| 摘 要： | 针对工业用水量的特点，建立了改进的BP神经网络用水量预测模型，采用遗传算法对BP神经网络权系进行优化改进，改进的BP神经网络算法预测结果好于灰色理论预测和BP算法预测。以本溪市某供水厂用水量数据对改进的BP神经网络模型进行训练并预测，将其预测结果与灰色理论预测和BP神经网络预测结果进行比较分析，得出该方法用于供水系统用水量预测误差较小，同时克服了其他两种算法的缺陷。 |
| 关 键 词： | 改进BP神经网络 用水量预测 遗传算法 灰色理论 |
| 文章编号： | 1008-0562(2004)02-0191-03 |
| 修稿时间： | 2003年3月21日 |
Forecast water consumption with improved BP neural network |
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| MA Feng-hai,YANG wei,YANG Fan ,YU Xiao-xi.Forecast water consumption with improved BP neural network[J].Journal of Liaoning Technical University (Natural Science Edition),2004,23(2):191-193. | |
| Authors: | MA Feng-hai YANG wei YANG Fan YU Xiao-xi |
| Institution: | MA Feng-hai1,YANG wei2,YANG Fan 4,YU Xiao-xi 3 |
| Abstract: | Based on the characteristics of water consumption, the paper established the model to forecast water consumption with the improved BP neural network and applied genetic algorithms to optimize the weight matrix. The forecast result shows that the improved BP neural network is better than the one only using the Grey theory forecasting or BP neural network forecasting. The model is trained with the water consumption data of Benxi Iron-steel Company and used to forecast water consumption. Comparing the forecast results with the Grey theory forecasting and BP algorithm it is concluded that the improved BP neural network model has the small error in forecasting water consumption, at the same time it can overcome shortcomings of other algorithms. |
| Keywords: | improved BP neural network water consumption forecasting genetic algorithms |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |