基于遗传算法的人工神经网络大气环境评价

人工神经网络模拟大脑的认知功能,通过改变连接点的权值和阈值来训练神经网络完成特定的功能。运用基于遗传算法的BP网络模型,以国家大气质量标准作为网络的输入样本对网络进行训练,对某地区大气质量进行评价,结果与综合指数法比较吻合。     

基于神经网络和遗传算法的城市火灾风险评价模型

以消防安全工程学与系统安全工程理论为基础,结合我国城市发展特征及消防安全管理状况,建立了城市区域火灾风险评价指标体系;针对神经网络易陷入局部极小而引起评价指标权值分布不合理的缺陷,提出了基于神经网络和遗传算法的城市火灾风险评价模型,该模型以火灾发生的可能性以及灾后的严重程度为输入单元,火灾风险等级为输出单元,采用误差反算法训练BP网络,最终得出火灾风险等级范围,有效地解决了城市火灾的动态性和非线性特征;研究实例证明了该模型的有效性,可为城市的消防安全管理提供确实可行的参考依据。     

提高洪水智能预报中洪峰预报精度方法的研究

针对防洪减灾的实际需要,对如何提高智能网络对洪峰的预报精度问题进行了深入系统的研究,提出了峰值放大修正系数和遗传算法优化网络初始权重相结合的改进算法,历史资料的检验结果表明了这些改进策略的有效性和可靠性.     

Predicting land cover using GIS, Bayesian and evolutionary algorithm methods

Modelling land cover change from existing land cover maps is a vital requirement for anyone wishing to understand how the landscape may change in the future. In order to test any land cover change model, existing data must be used. However, often it is not known which data should be applied to the problem, or whether relationships exist within and between complex datasets. Here we have developed and tested a model that applied evolutionary processes to Bayesian networks. The model was developed and tested on a dataset containing land cover information and environmental data, in order to show that decisions about which datasets should be used could be made automatically. Bayesian networks are amenable to evolutionary methods as they can be easily described using a binary string to which crossover and mutation operations can be applied. The method, developed to allow comparison with standard Bayesian network development software, was proved capable of carrying out a rapid and effective search of the space of possible networks in order to find an optimal or near-optimal solution for the selection of datasets that have causal links with one another. Comparison of land cover mapping in the North-East of Scotland was made with a commercial Bayesian software package, with the evolutionary method being shown to provide greater flexibility in its ability to adapt to incorporate/utilise available evidence/knowledge and develop effective and accurate network structures, at the cost of requiring additional computer programming skills. The dataset used to develop the models included GIS-based data taken from the Land Cover for Scotland 1988 (LCS88), Land Capability for Forestry (LCF), Land Capability for Agriculture (LCA), the soil map of Scotland and additional climatic variables.     

路面径流水环境下交通承载力分析

为了对路面径流水容许污染总量控制下的交通承载力问题进行探讨,利用神经网络具有的非线性映射能力和遗传算法具有的全局随机搜索能力,结合公路路面径流水质检测数据,提出了一种基于遗传神经网络进行公路交通环境承载力反计算的分析方法,应用该方法可根据路面径流水质污染数据反演出路段交通量大小,并可据此进行交通量与路而径流水质污染的关...     

遗传和模拟退火算法在水质模型参数确定中的应用简介

水质模型参数的确定是构建水质模型的基础。相对于传统优化方法,现代优化算法的优势日趋明显。本文在基于现代优化算法的水质模型参数确定研究背景下,介绍了具有代表性的遗传算法和模拟退火算法,并对该两种算法的应用现状进行综述,旨在推进该领域的进一步探索。     

ASSESSING FLOOD MITIGATION ALTERNATIVES IN SHIJR AREA IN METROPOLITAN TAIPEI1

The Keelung River Basin in northern Taiwan lies immediately upstream of the Taipei metropolitan area. The Shijr area is in the lower basin and is subject to frequent flooding. This work applies micromanagement and source control, including widely distributed infiltration and detention/ retention runoff retarding measures, in the Wudu watershed above Shijr. A method is also developed that combines a genetic algorithm and a rainfall runoff model to optimize the spatial distribution of runoff retarding facilities. Downstream of Wudu in the Shijr area, five dredging schemes are considered. If 10‐year flood flows cannot be confined in the channel, then a levee embankment that corresponds to the respective runoff retarding scheme will be required. The minimum total cost is considered in the rule to select from the regional flood mitigation alternatives. The results of this study reveal that runoff retarding facilities installed in the upper and middle parts of the watershed are most effective in reducing the flood peak. Moreover, as the cost of acquiring land for the levee embankment increases, installing runoff retarding measures in the upper portion of the watershed becomes more economical.     

基于遗传算法进行EMI滤波器电感的设计

通过电感的高频特性及其对共模插入损耗的影响分析,采用遗传算法和Ngspice仿真库设计出电感的选择方案,最后通过电路仿真和实验同时验证方案的有效性。该方案避免了对EMI滤波器高频段的复杂建模,降低了电感选择的难度,对电感元件的选择具有一定的指导意义。     

船舶区域溢油风险程度甄别的人工神经网络方法

利用误差反向传播 (BP)人工神经网络 ,建立了海域船舶溢油风险程度甄别的评价模型。该模型能够反映出研究海域各区域发生船舶溢油事件的风险等级差别 ,具有一定的客观性和实用性。     

TAGE:一种新的大气污染物来源及输送情况的网格化分析方法

提出了一种新的大气污染物来源及输送情况的网格化分析方法.首先,不依赖于排放源清单,而是以预设的网格化排放源来运行空气质量模型,得到排放源的污染影响因子.然后,结合污染物监测数据,构建排放源总合排放强度求解方程组,并利用遗传算法进行求解.最后,基于排放源的污染影响因子和总合排放强度,计算出排放源的污染贡献占比,从而完成对大气污染物来源及输送情况的网格化分析.这一方法的提出,为缺少准确排放源清单情况下大气污染状况的分析与治理,提供了新的思路.利用此方法,对北京市、石家庄市、保定市2017年10~12月期间PM_2.5的来源及输送情况进行了验证性实验.