【作者】 王静伟；

【导师】 金生；

【作者基本信息】 大连理工大学 ， 水力学与河流动力学， 2007， 硕士

【摘要】 近些年来，随着经济的发展和对大自然无休止的掠夺，我国大江大河流域内水土流失严重，造成大量的泥沙输入河道，加剧了江河整治的复杂性并带来严重的灾害。为了真正落实科学发展观与建设和谐社会，对于泥沙深入的研究迫在眉睫。虽然泥沙运动力学已形成了一些比较成熟的理论，但是至今仍有许多问题尚未得到解决。本文首先对泥沙的起动和推移质研究成果做简要的回顾性总结，并在此基础上详细阐述了泥沙起动问题和推移质问题联系的纽带——推移质最大起动粒径研究的意义以及就目前研究水平所面临的问题；与此同时，人工神经网络理论则模仿人脑的思维，做出判断和预测，它可以借助有限的实测资料获取经验，揭示输入资料潜在的效应和变化趋势，无需用户建立函数关系，对复杂的非线性系统尤为有效。其次，选择目前采用最为广泛的BP神经网络模型、通过VC#．NET开发平台和SQL2000数据库并结合平衡输沙状态下的水槽输沙试验数据，开发出界面友好、基于BP及其改进算法的多输入单输出三层神经网络预测软件。针对BP网络算法所固有的缺点，提出并实现的两种改进算法分别为自适应调整学习率算法和模拟退火算法。再次，利用作者开发的带有自主知识产权的预测软件和Matlab神经网络工具箱，对实验数据做计算、预测和分析；与此同时，针对BP算法的转换函数中参数t对网络模型输出精度和稳定性的影响展开探索性的研究，并在大量实验数据的基础上提出了参数t的取值公式与适用范围。最后，通过对基于经典BP网络算法、自适应调整学习率改进算法、模拟退火改进算法预测结果与Matlab神经网络工具箱预测结果之间科学详尽的横向与纵向的数据比较与稳定性分析得出本文的结论。本文的结论为：对于平衡状态下的宽级配非均匀沙水槽输沙试验中最大起动粒径的推求，利用VC#．NET开发出界面友好、基于BP及其改进算法的多输入单输出三层神经网络预测软件，其计算精度满足工程要求，特别对模拟退火改进算法，其计算精度比成熟的Matlab工具箱神经网络工具箱计算精度还要高，显示出光明的应用前景与商业价值，对于泥沙起动和推移质的研究有一定的辅助作用和参考价值。更多还原

【Abstract】 Recent years, along with the development of economy and the endless depredation of nature, the phenomenon of water and soil loss in our country is more and more serious, which causes much more sediment into the rivers .That arouses the complexity of management to the rivers and many more severe disasters. For the sake of scientific development outlook and a harmonious society, deeper in investigation of sediment is imperatively. But, unfortunately, the problems about sediment science have not been solved completely until now.The main contents are as follows: First of all, on the basis of comprehensive review of the study achievements on sediment motion and transport, this dissertation elaborates the maximal grain size during incipient motion (MGSIM), which is the connection between sediment motion and sediment transport, moreover, this dissertation also analyses the traditional investigations of MGSIM, which are also faced with a lots of problems; at the same time, artificial neural network (ANN) is an approximate simulation of biologic nerve system, which is a network model with a special algorithm got from biologic prototype after abstractly research. This dissertation chooses the BP algorithm which is a most popular and mature artificial neural network model. The author uses VC#.NET platform, SQL2000 database system and the experiment data (the gross bed-load transport rate of Non-uniform sediment with a wide distribution in flume) to develop the forecast software, which is friendly-interface, multi-input, single output, three layers’ artificial neural network base on BP and improved BP algorithms. Aiming at the classical BP algorithm’s limitation, the dissertation introduces and realizes two improved BP algorithms, which are called self-adapting adjust rate algorithm and simulated annealing algorithm. Secondly, the applications of BP and improved BP algorithms in sediment science are by using the self-determination intellectual property forecast software and Matlab neural network toolbox to compute, forecast and analyze the experiment data; on the other hand, the dissertation probes into a parameter (t) of diversion function about BP algorithm. It discusses and analyses the relationship between t and computation precision of BP algorithm on the basis of abundant experiment data, furthermore it proposes a formula for values of t independently. Thirdly, the results which are computed by classical BP algorithm, self-adapting adjust rate algorithm, simulated annealing algorithm and Matlab neural network toolbox respectively compare with each other in transverse and longitudinal ways.Lastly, it draws conclusion as follows: computation in Non-uniform sediment with a wide distribution in flume experiment of stead sediment transportation by the software which is developed by VC#.NET platform satisfies with requirement of engineering, especially the simulated annealing algorithm, its stability of the network and precision of computation are superior to Matlab neural network toolbox. Those conclusions show that the applications of BP and improved BP algorithms in sediment science are feasible and also both have more values of investigation and commerce, besides, the software can be an auxiliary and referenced tool for sediment science research.更多还原