应用遗传神经网络方法分析我国降水化学数据

收集了１１１组包含Ｃａ＾２＋、Ｍｇ＾２＋等８种离子浓度和ＰＨ值的我国降水化学数据，并用遗传神经网络（Ｇｅｎｅｔｉｃ Ｎｅｕｒａｌ Ｎｅｔ－ｗｏｒｋｓ，ＧＮＮ）方法建立了这些离子浓度和ＰＨ值绵ＢＰ网络模式，运用这些模式计算了各离子浓度对ＰＨ值的贡献，结果表明，我国各地降水ＰＨ值与各地区酸性离子与碱性离子相互用途相关，其中生离子的中和作用起着主导作用。     

马斯京根模型参数估计的新方法

提出了马斯京投模型参数估计的一种新方法—加速遗传算法,分析了该算法控制参数的优化特性,总结出了这些参数的简便设置技术．应用实例表明,该方法简便、直观、通用、适应性强,它可广泛应用于各种自然灾害模型的优化问题之中。     

遗传算法在二氧化硫总量控制中的应用研究

污染物总量控制是目前我国广泛应用的一种控制区域环境质量达标的方法,为了实施城市大气污染物排放总量控制,实现各功能区污染物浓度达标,采用浓度控制与总量控制相结合的方法。本文提出利用遗传算法进行大气污染总量控制,并在传统遗传算法的基础上做了改进,提出基因库和基因重组的方法。     

黄河流域水资源承载力评价

定量评价水资源承载力,可为有效调控水资源,提高水资源承载力和消除水资源超载区提供依据。从水资源承载力新内涵出发,构建“量—质—域—流”的四维水资源承载力评价指标体系,确定指标评价等级标准。针对水资源承载力评价涉及许多不确定因素以及指标间存在耦合关系等特点,采用可考虑指标间耦合关系的EFAST算法计算权重,结合可处理评价不确定性问题的联系熵模型进行水资源承载力评价。以黄河流域为例,计算得权重与熵权法进行比较,对2015年流域61个地市的水资源承载力状况进行了综合评价。结果表明：EFAST算法计算权重比熵权法更合理;黄河流域水资源承载力处于Ⅰ级（极高）、Ⅱ级（较高）、Ⅲ级（中等）、Ⅳ级（较低）和Ⅴ级（极低）的地市数量占评价总地市数的比例分别为0、4.9%、18.1%、63.9%和13.1%,其中Ⅳ级和Ⅴ级分布在除青海省外的其他省区的地市。     

A spatial zero-inflated poisson regression model for oak regeneration

Ecological counts data are often characterized by an excess of zeros and spatial dependence. Excess zeros can occur in regions outside the range of the distribution of a given species. A zero-inflated Poisson regression model is developed, under which the species range is determined by a spatial probit model, including physical variables as covariates. Within that range, species counts are independently drawn from a Poisson distribution whose mean depends on biotic variables. Bayesian inference for this model is illustrated using data on oak seedling counts. Received: May 2004 / Revised: December 2004     

Design of a water quality monitoring network in a large river system using the genetic algorithm

Despite several decades of operations and the increasing importance of water quality monitoring networks, the authorities still rely on experiential insights and subjective judgments in siting water quality monitoring stations. This study proposes an integrated technique which uses a genetic algorithm (GA) and a geographic information system (GIS) for the design of an effective water quality monitoring network in a large river system. In order to develop a design scheme, planning objectives were identified for water quality monitoring networks and corresponding fitness functions were defined using linear combinations of five selection criteria that are critical for developing a monitoring system. The criteria include the representativeness of a river system, compliance with water quality standards, supervision of water use, surveillance of pollution sources and examination of water quality changes. The fitness levels were obtained through a series of calculations of the fitness functions using GIS data. A sensitivity analysis was performed for major parameters such as the numbers of generations, population sizes and probability of crossover and mutation, in order to determine a good fitness level and convergence for optimum solutions. The proposed methodology was applied to the design of water quality monitoring networks in the Nakdong River system, in Korea. The results showed that only 35 out of 110 stations currently in operation coincide with those in the new network design, therefore indicating that the effectiveness of the current monitoring network should be carefully re-examined. From this study, it was concluded that the proposed methodology could be a useful decision support tool for the optimized design of water quality monitoring networks.     

Genetic Algorithm Usage in Water Quality Monitoring Networks Optimization in Gediz (Turkey) River Basin

Selection procedure of the optimum station combination for decreasing the station number from 33 to 14 in water quality monitoring network of Gediz river basin was applied using an optimization method. Gediz basin is one of the important basins and it covers 2.3% of the total surface area of Turkey. The technique includes two stages as the data preparation and the optimization. In the data preparation stage, firstly, alternative station combinations decreased and then station combination scores obtained from assigned selection criteria for point and nonpoint pollution management objectives. Finally, genetic algorithm applied to select the best combination. The results were compared with a prior solution that used dynamic programming as the optimization technique.     

基于时间的进场航班效率评估方法研究

终端区作为空中交通的起讫点,是拥堵、延误的多发区,其运行效率对航班整体的运行效率至关重要。欧洲航行安全组织(EUROCONTROL)采用畅通进场时间(Unimpeded AMSA Time)作为量化进场效率的标杆。我国目前还没有明确的进场效率量化指标,因此可以借鉴畅通进场时间这个指标来评估进场效率。以首都机场为研究对象,首先对进港航班ADS-B数据进行预处理来计算进场时间,然后利用K-means聚类算法对航班进行分组,运用回归分析法找寻与终端区拥挤程度关联性最强的解释变量,提出关于畅通航班拥挤阈值的方法来计算畅通进场时间,最后用时间效率指标对进场效率进行评估,得出5月首都机场的进场效率为83. 39%,可为进场效能评估提供参考。     

路径-脆弱点最短距离最大化的危险品运输网络设计

为了实现危险品运输网络的有效设计,进而降低危险品运输风险。将分布于公路两侧的医院、学校、居民区、购物中心等人口集聚场所定义为“脆弱点”,并通过计算运输路径和脆弱点间的加权距离来评估路段风险;结合双层理论构建模型,上层规划为政府的网络设计问题,通过关闭部分路段来最大化危险品车辆行驶路径与各脆弱点间的最小加权距离,下层规划则为承运商的车辆路径选择问题;为求解模型,设计1类启发式算法,并对算法的计算时间复杂性进行证明,最后根据算例分析发现,该算法经过有限数量的迭代即可得到风险最小的、次小的、…、第k小的运输路径及对应的路段关闭方案,为寻求兼顾运输风险和运输成本的最优方案提供决策支持。     

基于遗传算法的大庆市黎明河环境需水量优化配置

为克服水环境管理领域中多目标优化模型加权法求解时主观性强的缺点,将遗传算法与河流水质模拟模型相耦合用于大庆市黎明河生态环境水量优化配置的研究。该模型充分利用遗传算法的开放性和全局搜索的能力,从而得到了较满意的调水方案。对调水方案实施后的河流水质状况进行仿真的结果表明,水质有明显的改善,从而进一步证实了遗传算法应用于城市内河的生态环境水量优化配置的可行性和有效性。