并建立起一套系统的城市生活需水量预测方法，为城市水资源规划提供决策参考，具有理论和实践意义。
A systematic forecast method for city life water requirement is established, and it has theoretical and practical significance to provide a reference for city water resources programming.
结果表明，应用系统动力学模型预测城市需水量，系统性强，预测结果准确度高。
The result shows that application of system dynamics model to predict urban water demand has the advantages of strong systematicness and high accuracy of prediction result.
研究了灰色系统理论在中长期城市需水量预测中的应用。
The application of Grey Theory in the prediction of medium and long-term urban water demand is studied in this paper.
要进行科学、高效的灌溉管理，必须准确地计算和预测作物需水量。
In order to carry through scientific and efficient irrigation management, crop water requirements must be calculated and forecasted accurately.
本文主要介绍基于人工神经网络需水量的预测方法，并对其进行综合评价与分析。
In this paper, we mainly introduce the method of water demand prediction based on the artificial neural network, and further we evaluate and analyse it.
以青岛市为研究对象，对其工业需水量进行了预测研究，预测方法采用灰色预测理论。
Taking Qingdao as the research object, the forecast research on its industrial water demand is conducted, the method of prediction USES the grey prediction model.
用该模型对西安和北京两地的生活需水量进行预测，结果表明该模型进行生活需水量预测是可行的。
Using the model, domestic water demands in Xi 'an and Beijing have been predicted, the results have shown that this model was available to predict domestic water demand.
将优选出的模型应用于疏勒河灌区的作物需水量预测，为灌区作物灌溉提供指导。
The optimized model is applied to predict the crop water requirements of Shulehe irrigation area to provide guidance for crop irrigation in the irrigation area.
介绍工业需水量预测的主要方法，综合分析工业需水量预测中的风险因素。
This paper introduces the main method to predict industrial water requirement, to analyse totally risk factors in prediction of industrial water requirement.
用该模型对西安和北京两地的生活需水量进行预测，结果表明该模型进行生活需水量预测是可行的。
Using the model, domestic water demands in Xi 'an and Beijing have been predicted, the results have shown that this model was av...
将小波分析理论、灰色预测理论和时间序列预测法组合进行需水量的预测，为原始非平稳时间序列的预测应用拓展了空间。
The space of prediction and application of non-stationary time series were expanded through the combined model of wavelet analysis, gray and time series prediction methods.
将小波分析理论、灰色预测理论和时间序列预测法组合进行需水量的预测，为原始非平稳时间序列的预测应用拓展了空间。
The space of prediction and application of non-stationary time series were expanded through the combined model of wavelet analysis, gray and time series prediction methods.
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