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1.
人工神经网络与遗传算法在多泥沙洪水预报中的应用   总被引:6,自引:6,他引:10  
由于水沙作用机制和演进规律的复杂性,以及河道形态变化等因素,多泥沙洪水预报一直是洪水预报的难点,对高含沙洪水快速、准确的预报是多年来国内外专家十分关注的课题。作者采用具有高度非线性识别能力的人工神经网络与遗传算法相结合的方法,探讨了建立智能预报模型的基本方法,进一步对如何提高预报精度的问题进行了研究,并结合黄河洪水预报实例检验了神经网络模型的可行性。检验结果表明,该方法能够较好地识别多泥沙洪水的演进规律,对水位、流量和含沙量都能进行合理预报。  相似文献
2.
Genetic Algorithm for Optimal Operating Policy of a Multipurpose Reservoir   总被引:6,自引:6,他引:3  
This paper presents a Genetic Algorithm (GA) model for finding the optimal operating policy of a multi-purpose reservoir, located on the river Pagladia, a major tributary of the river Brahmaputra. A synthetic monthly streamflow series of 100 years is used for deriving the operating policy. The policies derived by the GA model are compared with that of the stochastic dynamic programming (SDP) model on the basis of their performance in reservoir simulation for 20 years of historic monthly streamflow. The simulated result shows that GA-derived policies are promising and competitive and can be effectively used for reservoir operation.  相似文献
3.
基于改进层次分析法的模糊综合评价模型   总被引:5,自引:5,他引:92  
模糊综合评价在理论和应用中的关键问题是如何合理确定各评价指标的权重。为此,提出了直接根据单指标相对隶属度的模糊评价矩阵,构造层次分析法中的判断矩阵,用以确定各评价指标权重。给出了用加速遗传算法检验和修正判断矩阵的一致性和计算判断矩阵各要素的权重的模糊综合评价模型(AHP_FCE)。实例表明,AHP_FCE方法简便和通用,计算结果较为客观和稳定,在系统工程理论和实践的各种综合评价中具有推广应用价值。  相似文献
4.
Genetic algorithms (GA) have been widely applied to solve water resources system optimization. With the increase of the complexity and the larger problem scale of water resources system, GAs are most frequently faced with the problems of premature convergence, slow iterations to reach the global optimal solution and getting stuck at a local optimum. A novel chaos genetic algorithm (CGA) based on the chaos optimization algorithm (COA) and genetic algorithm (GA), which makes use of the ergodicity and internal randomness of chaos iterations, is presented to overcome premature local optimum and increase the convergence speed of genetic algorithm. CGA integrates powerful global searching capability of the GA with that of powerful local searching capability of the COA. Two measures are adopted in order to improve the performance of the GA. The first one is the adoption of chaos optimization of the initialization to improve species quality and to maintain the population diversity. The second is the utilization of annealing chaotic mutation operation to replace standard mutation operator in order to avoid the search being trapped in local optimum. The Rosenbrock function and Schaffer function, which are complex and global optimum functions and often used as benchmarks for contemporary optimization algorithms for GAs and Evolutionary computation, are first employed to examine the performance of the GA and CGA. The test results indicate that CGA can improve convergence speed and solution accuracy. Furthermore, the developed model is applied for the monthly operation of a hydropower reservoir with a series of monthly inflow of 38 years. The results show that the long term average annual energy based CGA is the best and its convergent speed not only is faster than dynamic programming largely, but also overpasses the standard GA. Thus, the proposed approach is feasible and effective in optimal operations of complex reservoir systems.  相似文献
5.
应用单亲遗传算法进行树状管网优化布置   总被引:4,自引:4,他引:26  
周荣敏  林性粹 《水利学报》2001,32(6):0014-0019
树状管网布置优化属于典型的组合优化问题。本文针对树状管网布置的特点,以图论和遗传算法为理论基础,应用改进遗传算法 单亲遗传算法进行树状管网优化布置,并设计了相应的适应度函数、单亲换位算子和逆转算子。与Dijkstra算法和Kruskal算法相比,单亲遗传算法直接以管网投资最小为优化目标,能够获得一批管网投资最小的布置方案,且算法的寻优效率较高,收敛性和稳定性较好。  相似文献
6.
章少辉  许迪  李益农  蔡林根 《水利学报》2006,37(11):1297-1302
利用基于地表非稳定流运动方程的地面灌溉模型对畦灌性能进行分析评价是改进传统地面灌溉方式、提高畦灌性能的重要举措,而准确地确定畦灌土壤入渗参数和田面糙率系数是改善畦灌性能模拟精度的重要前提。本文基于基本遗传算法SGA和地面灌溉一维模型SRFR建立的畦灌土壤入渗参数与田面糙率系数优化反演模型,可在给定的参数值域范围内开展多参数全局性寻优,利用计算机动态解析技术对SRFR模型执行程序进行解析处理,建立SGA与SRFR模型间的内部运行衔接方式,实现畦灌土壤入渗参数与田间面糙率系数优化反演过程的自动化运作,进而有效提高了参数寻优估值的工作效率。  相似文献
7.
A comprehensive Genetic Algorithm (GA) model has been developed and applied to derive optimal operational strategies of a multi-purpose reservoir, namely Perunchani Reservoir, in Kodaiyar Basin in Tamil Nadu, India. Most of the water resources problem involves uncertainty, in order to see that the GA model takes care of uncertainty in the input variable, the result of the GA model is compared with the performance of a detailed Stochastic Dynamic Programming (SDP) model. The SDP models are well established and proved that it takes care of uncertainty in-terms of either implicit or explicit approach. In the present study, the objective function of the models is set to minimize the annual sum of squared deviation from desired target release and desired storage volume. In the SDP model the optimal policies are derived by varying the state variables from 3 to 9 representative class intervals, and then the cases are evaluated for their performance using a simulation model for longer length of inflow data, generated using a Thomas–Fiering model. From the performance of the SDP model policies, it is found that the system encountered irrigation deficit, whereas GA model satisfied the demand to a greater extent. The sensitivity analysis of the GA model in selecting optimal population, optimal crossover probability and the optimal number of generations showed the values of 150, 0.76 and 175 respectively. On comparing the performance of SDP model policy with GA model, it is found that GA model has resulted in a lesser irrigation deficit. Thus based on the present case study, it may be concluded that the GA model performs better than the SDP model.  相似文献
8.
基于可行空间搜索遗传算法的水库调度图优化   总被引:3,自引:3,他引:0  
本文从调度图概化、调度图模拟模型、目标函数以及优化算法等方面全面介绍了基于可行空间搜索遗传算法的调度图优化模型的原理及建模方法。针对调度图优化问题可行空间搜索困难的特点,在传统遗传算法概念基础上提出了可行空间搜索的概念。根据决策变量间的几何关系,设计了调度图优化问题的编码结构以及信息交互机制,以NSGA-Ⅱ算法为基础实现了优化模型的构建。将研究成果应用于寺坪水库调度图优化,与设计调度图模拟结果相比,发电效益及保证率均得到了明显提高。  相似文献
9.
基于模拟退火遗传算法的自压树状管网优化   总被引:3,自引:3,他引:5  
将遗传算法全局优化和模拟退火的良好局部搜索能力有机结合,构造出一种退火遗传算法用于自压树状管网的优化设计方法。假定管网中每一管段最多只能由两种管径的管道组成,建立了以管网造价为目标函数,以管长、标准管径为决策变量的自压树状管网优化数学模型。采用基于不可行度的退火算法处理约束条件,应用遗传算法进行优化计算。仿真实例结果表明,该模型与算法在求解自压树状管网优化问题上,具有良好的优化性能和求解效率。  相似文献
10.
遗传算法在水库(群)优化调度研究中的应用综述   总被引:3,自引:3,他引:3  
介绍了遗传算法在水库(群)优化调度中的应用背景及算法的收敛性,讨论了水库(群)优化调度中遗传算法的基本应用步骤以及存在的问题,给出了算法的各种改进方法,并对遗传算法的应用前景进行了展望.  相似文献
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