【摘要】 水资源是支撑人类生存和社会持续发展的最基本的自然资源,中长期径流预报可以为水资源的保护、开发、管理提供重要参考。中长期径流预报是对预见期超过流域最大汇流时间的径流,基于一定的数学模型进行预测,其预测结果可以为制定水资源系统的中长期运行方案提供重要依据,并被广泛的应用于水库调度、水电站运行、防洪抗旱、水资源调配和航运管理等领域中。然而预见期较长,众多影响因素导致径流形成过程十分复杂,同时人类的生产活动不断深入,使得中长期径流预报结果的精度往往不高。本文尝试将粗糙集理论引入到中长期径流预报的研究中,从历史径流资料中挖掘最有影响的因素,删除影响较小的因素,然后基于核心因素集,使用支持向量回归模型进行径流预测。同时基于Flex技术,设计并开发了具有强大交互能力和丰富页面呈现能力的中长期径流预报系统,为相应的水电优化调度提供支持。本文的工作和研究成果主要体现在以下几个方面:1)将粗糙集理论引入到中长期径流预报的研究中,并结合新疆伊犁河雅马渡站的年径流资料进行了建模与应用。使用基于类信息熵的算法进行条件属性离散,采用遗传算法对条件属性进行约简,获得与径流量相关的核心因素集。由于粗糙集理论无需提供问题所需处理的数据集合之外的任何附加信息,因此对中长期径流预报问题的不确定性描述和处理是比较客观的。同时使用粗糙集理论进行属性约简,消除冗余信息,使SVM的训练数据大大减少,提高了系统的运行速度。2)由于粗糙集理论只能处理离散化数据,且抗干扰能力差,本文引入SVM理论来获得径流预测值。将SVM作为粗糙集预处理的后置系统,具有良好的容错和抗干扰能力。其中采用遗传算法和交叉验证来对SVM的相关参数进行寻优,摆脱了以往参数选择的盲目性和主观性,提高了预报精度。预报结果表明将粗糙集理论和SVM算法结合起来用于中长期径流预报,预测系统具有较好的泛化和抗干扰能力,并获得了良好的预报性能。3)基于Flex技术开发中长期径流预报系统,充分利用了其强大的组件库,以及灵活的自定义组件,构建了具有丰富图表交互能力的WEB应用程序,具备良好的用户体验。采用Flex技术开发的WEB应用程序,彻底地实现了MVC架构,把控制用户操作的逻辑从服务器端代码中完全分离出来,系统层次结构清晰。同时Flex技术将数据与界面组件紧密联系起来,并采用异步方式与服务器进行通信,在数据传输过程中用户不需要中断操作来等待数据刷新。4)在中长期径流预报系统的服务器端使用JNI技术调用预报算法动态链接库文件。预报算法库文件是已有的旧模块,采用C++语言编写,这在一定程度上弥补了Java语言在程序运行性能上的不足,提高了算法的运算速度,而且使用动态链接库封装算法,也在很大程度上保护了预报算法的知识产权,这样在保证系统功能实现的基础上,缩短了开发周期,降低了开发成本,保护了历史投资。 更多还原
【Abstract】 Water resource is essential for human being and the society’s sustainable development. The mid-long term runoff forecasting is important for the protection, exploitation, management of water resource, it uses mathematical models to forecast runoff, and the forecast period preponderats over the maximum concentration time of the watershed. Its result provids an important basis for the mid-long term operation of water resource, and is widely used in the fields of reservoir operation, hydropower scheduling, flood control and drought combat, allocation of water resource, shipping management. However, due to the long forecast period, and the complexity of the formation mechanism of runoff, coupled with the impact of human production activities, the accuracy of the mid-long term runoff forecasting is not high.This paper introduces the rough set theory to the mid-long term runoff forecasting, selects the most influential fators from the historical runoff data, excludes secondary factors, then uses support vector regression model to predict runoff based on the core factor set. By using Flex, it designs and develops a mid-long term runoff forecasting system, which has the strong mutual ability and the rich rendering ability, and the system can support the optimal scheduling of hydropower. The main works and research achievements are as follows:1)The rough set theory is proposed for the study of the mid-long term runoff forecasting. The paper introduces its modeling and application with the yearly runoff data of the Yamadu station on Yili river in Xinjiang. It uses an algorithm based on the class-information entropy for the discretization of condition attributes, and a genetic algorithm is used for attribute reduction, then the core factor set would be gained. As the rough set doesn’t need any additional information outside the necessary data collection, its description and processing for the issue of mid-long term runoff forecasting are very objective. The rough set discretizes attributes, eliminates redundant information, it reduces training data for SVM significantly, and thses improve the system’s speed.2)As the rough set can only deal with discrete data,and its anti-interference ability is poor, the SVM theory is proposed for runoff forecasting. The SVM as a post-system has good fault tolerance and anti-interference capability. It uses genetic algorithm and cross validation to optimize the relevant parameters.It gets rid of the blindness and subjectivity on parameters selection, and improves the prediction’s accuracy. The forecasting results show that the rough set combining with the SVM has better generalization and anti-interference capability and gains a good prediction performance.3)A mid-long term runoff forecasting system has been developed with Flex. Flex has a powerful component library and can make custom components flexibly. The system is a web application, which has the strong mutual ability ,the rich rendering ability and a perfect user experience. The Web application, which is developed by Flex, implements the MVC framework, and separates the user control logic from the server code, so the system’s structural levels are clear. Flex links data with the interface components closely, the client communicates with the server asynchronously. The user doesn’t need to stop for data refresh when the data is transporting.4)The mid-long term runoff forecasting system calls the algorithm dynamic link libraries with JNI in the server-side. The libraries which are written by C++, are old modules. They make up for the shortage of Java’s performance, improve the operation speed, and also protect the intellectual property of the prediction algorithms. On the basis of ensuring the system’s functions, they shorten the development cycle, reduce the costs, and protect the historical investment. 更多还原
【关键词】 中长期径流预报； 粗糙集； Flex； 支持向量回归；
【Key words】 mid-long term runoff forecasting； rough set； Flex； support vector regression；
粗糙集理论和Flex技术在中长期径流预报中的应用
【目录】摘要 4-6
Abstract 6-7
1 绪论 10-16
1.1 选题背景 10-11
1.2 中长期径流预报研究现状综述 11-14
1.3 本文主要研究内容 14-16
2 粗糙集、支持向量回归和 Flex 的相关知识 16-29
2.1 粗糙集理论 16-24
2.2 支持向量回归算法 24-27
2.3 Flex 技术 27-29
3 粗糙集理论在中长期径流预报中的应用 29-56
3.1 应用粗糙集理论进行中长期径流预报的可行性分析 29-30
3.2 数据选取及模型建立 30-32
3.3 属性离散 32-34
3.4 属性约简 34-40
3.5 SVM 回归算法的应用 40-42
3.6 径流预报结果分析 42-56
4 基于 Flex 技术的中长期径流预报系统的设计与实现 56-77
4.1 富互联网应用——RIA 56
4.2 开发环境及配置 56-57
4.3 关键技术 57-63
4.4 系统架构 63-70
4.5 主要功能界面展示 70-77
5 总结与展望 77-79
5.1 全文总结 77-78
5.2 展望 78-79
致谢 79-80
参考文献 80-86
附录 攻读硕士学位期间发表的学术论文 86
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