| 1. | Hourly water demand forecast model based on least squares support vector machine
基于最小二乘支持向量机的时用水量预测模型 |
| 2. | Hourly water demand forecast model based on bayesian least squares support vector machine
基于贝叶斯最小二乘支持向量机的时用水量预测模型 |
| 3. | Water demand forecasting and water price are two important parts of water resources management
用水量预测和水价是水资源管理的两个重要内容。 |
| 4. | In order to improve urban water demand forecasting precision , classified - forecasting method is presented
为了进一步提高预测精度，本文提出了采用分类预测方法对城市需水量进行预测。 |
| 5. | With its application in daily water demand forecast , daily water demand forecast is separated into domestic water consumption , industrial water consumption , commercial water consumption and common water consumption . it proved that the forecasting precision has been more accurate in a certain extent
并通过对日需水量按照生活、工业、商业和公共用水分别进行预测，结果证明分类预测能使预测精度在一定程度上得到改善。 |
| 6. | On the basis of urban water demand forecasting methods " studying , and activex controls integrated , urban water demand forecasting system for shenzhen is developed by using visual basic , sql server and matlab as the developing stage . the system , which offers a simple and efficacious way to develop software , is effective in timely optimal control of water supply system , and the system is worth referring to while developing other optimal dispatching software such as water supply system
在对城市需水量预测方法研究的基础上，本文选用visualbasic 、 matlab 、 sqlserver为开发平台，结合activcx技术开发了深圳特区需水量预测系统，为实现输配水系统的实时优化调度奠定了基础，有良好的实用价值，也提供了一种简单高效的软件开发思路，对于给水系统其它优化调度软件的开发也具有很好的参考价值。 |
| 7. | On the basis of analyzing historical water consumption in shenzhen , hourly water demand , daily water demand and annual water demand are studied using non - linear regression model , time series model , artificial neural network , gray model and compounding model , etc . by anglicizing merits and demerits of every model in different forecasts , time series model is appropriate to hourly water demand forecast ; compound forecasting model of time series and regress analysis is appropriate to daily water demand forecast ; gray model and regress analysis model is appropriate to annual water demand forecast
本文通过分析深圳特区用水量的变化规律，采用非线性回归分析、时间序列、人工神经网络、灰色模型和组合预测模型分别对时需水量、日需水量、年需水量进行了研究。通过比较分析各种模型在不同预测类型中的优缺点，时需水量预测较适合采用时间序列模型；日需水量预测较适合采用时序?回归分析组合预测模型；年需水量预测较适合灰色模型、回归分析模型；提出了指导选择城市需水量预测模型的方法。 |
| 8. | According to the hourly water demand forecasting results of hangzhou city , the reasonability and effectiveness of this model was proved . real large water supply system is a complicatedly dynamic nonlinear system , it is influenced by many factors , and these factors are interactional . it is difficult to simulate water distribution networks by using one or several explicit functions
由于实际大型供水系统是非常复杂的动态非线性系统，在实际管网的运行中，受到多因素的制约和影响，各综合因素作用叠加起来造成水流状态极其复杂，使得很难以一个或几个统一的显式函数关系描述管网的工况。 |
| 9. | Then based on the water demand forecasting , a mathematical model on water supply network , is established . also the basic theory of aga is presented . the control effect is ameliorated greatly through the improvement on objective function and several steps of algorithm
本文首先介绍了管网调度的国内外概况，随后在用水量预测的基础上，建立管网调度数学模型；接着介绍了加速遗传算法的基本理论，在此基础上，通过对目标函数的改进，对算法部分步骤的改进，使得改进的加速遗传算法调度效果更好。 |
| 10. | Urban water demand forecasting can be assorted into annual water demand forecasting and hourly water demand forecasting , daily water demand forecasting . they are efficient means of programming and managing of urban water resource , and they are important portion of optimizing dispatching management of water supply system
城市需水量预测可分为中长期的年需水量预测以及短期的时需水量预测、日需水量预测，它们是城市进行水资源规划和管理的有效手段，也是供水系统优化调度管理的重要部分。 |
