【摘 要】
：
针对目前中长期灌溉制度制定方法的不足,提出了基于降水过程和作物需水过程的年型判别模型,并以此为基础,利用云推理模型预测出未来年份的年型,在与其年型相近的历史年份中选
【机 构】
：
西安理工大学水利水电学院,北京师范大学水科学研究院,华北水利水电学院水利学院,
论文部分内容阅读
针对目前中长期灌溉制度制定方法的不足,提出了基于降水过程和作物需水过程的年型判别模型,并以此为基础,利用云推理模型预测出未来年份的年型,在与其年型相近的历史年份中选出最合适的,将该年的灌溉制度应用于未来年.实例表明:基于来水和需水过程的年型判别模型更加符合实际,而云推理模型很擅长从大量数据中挖掘出不确定性知识,两者结合选择出的中长期灌溉制度能够更好的指导生产实践,有较高的推广应用价值.
In view of the shortages of the current medium and long-term irrigation system formulation methods, the annual discriminant model based on precipitation process and crop water demand process is proposed. Based on this, the model of predicting future years is predicted by using cloud reasoning model. The most appropriate year is selected from the historical years, the irrigation system of the year is applied in the future years.Examples show that the year-type discriminant model based on incoming water and water-demand process is more realistic and the cloud reasoning model is good at extracting data from large amounts of data Digging out the knowledge of uncertainty, the combination of the two medium and long-term irrigation system can better guide the production practice, have a higher value of popularization and application.
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