A FAST RECURSIVE GIS ALGORITHM FOR COMPUTING STRAHLER STREAM ORDER IN BRAIDED AND NONBRAIDED NETWORKS1

ABSTRACT: Stream ordering is a useful property of every river network, having a wide range of applications. A method for determining stream orders that quickly and easily addresses various network topologies and magnitudes is therefore needed. This paper introduces a general recursive stream ordering framework for vector hydrography. It also presents a linear, O(n), stream ordering procedure for braided river networks, which is a major improvement to the existing quadratic, O(n²), procedure. The discussion includes results and interpretations, and the appendices present procedure pseudocodes and thorough line by line explanations.     

OPTIMIZATION PROCEDURE FOR COST EFFECTIVE BMP PLACEMENT AT A WATERSHED SCALE1

ABSTRACT: A combinatorial optimization procedure for best management practice (BMP) placement at the watershed level facilitates selection of cost effective BMP scenarios to control non point source (NFS) pollution. A genetic algorithm (GA) was selected from among several optimization heuristics. The GA combines an optimization component written in the C++ language with spatially variable NFS pollution prediction and economic analysis components written within the Arc View geographic information system. The procedure is modular in design, allowing for component modifications while maintaining the basic conceptual framework. An objective function was developed to lexicographically optimize pollution reduction followed by cost increase. Scenario cost effectiveness is then calculated for scenario comparisons. The NPS pollutant fitness score allows for evaluation of multiple pollutants, based on prioritization of each pollutant. The economic component considers farm level public and private costs, cost distribution, and land area requirements. Development of a sediment transport function, used with the Universal Soil Loss Equation, allows the optimization procedure to run within a reasonable timeframe. The procedure identifies multiple near optimal solutions, providing an indication of which fields have a more critical impact on overall cost effectiveness and flexibility in the final solution selected for implementation. The procedure was demonstrated for a 1,014‐ha watershed in the Ridge and Valley physiographic region of Virginia.     

预测低温冷害的门限回归模型

提出用门限回归模型（TR）来描述低温灾害指标变量在灾害状况与非灾害状况的突变性。研制了TR建模的一套简便通用的方案，用笔者改进的遗传算法可同时优化门限值和回归系数，从而解决了TR建模过程所涉及的大量复杂寻优工作这一问题，为TR模型的广泛应用提供了有效工具。实例的计算结果说明了其可行性和有效性。该方案具有通用性，在各种自然灾害时序预测中具有广泛的实用价值。     

基于遗传算法与人工神经网络相结合的玉米估产研究

在遗传算法 (GeneticAlgorithm )与误差反传 (BackPropagation)网络结构模型相结合的基础上 ,设计了用遗传算法训练神经网络权重的新方法 ,并对吉林省梨树县的玉米进行了估产研究 ,同时与BP算法和灰色系统理论模型进行了比较。经检验 ,计算值与实际值接近 ,并优于灰色理论模型 ,具有良好的预测效果 ,从而为农作物估产提供了新方法     

BP人工神经网络模型在拉萨道路交通噪声预测中的应用

针对拉萨市道路交通噪声污染问题,运用人工神经网络理论和方法对拉萨市道路交通噪声的等效连续声级进行预测.经检验,计算值与实测值接近,从而为道路交通噪声的预测提供了一种新的途径.     

BP人工神经网络模型在拉萨道路交通噪声预测中的应用

针对拉萨市道路交通噪声污染问题，运用人工神经网络理论和方法对拉萨市道路交通噪声的等效连续声级进行预测。经检验，计算值与实测值接近，从而为道路交通噪声的预测提供了一种新的途径。     

二维水质模型横向扩散系数的人工神经网络模拟

将人工神经网络的理论和方法引入河流横向扩散系数的理论预测中，提出了基于BP人工神经网络的横向扩散系统预测模型，应用国内外河流的实测样本对模型进行训练与检验表明，该模型用于横向扩散系数的计算不仅可行而且精度较高，为河流横向扩散系数预测研究开辟了新途径。     

加速基因算法在海洋环境预报中的应用

基于自然选择和自然基因机制的基因算法是一种优秀的寻优方法，它利用遗传操作算子来模拟生物界的优生劣汰的规律，是一种多路径全局优化方法。为增强经典基因算法对实际模型参数变化范围的适应性，加快其全局寻优速度和简化算法参数设置技术，本文给邮了一种改进基因算法，并在海渔期预报，冰情预报中得到成功应用。该法可广泛用于各种工程模型优化之中。     

B－P网络用于水质综合评价方法的研究

本文应用误差反向传播（Ｂ—Ｐ）算法的人工神经网络建立了水质综合评价模型。该模型应用于实例的水质评价结果表明Ｂ—Ｐ网络用于水质综合评价具有客观性和实用性。     

基于粗集、遗传神经网络的环境质量评价

基于粗集、遗传神经网络的环境质量评价方法利用粗集对属性的归约功能将数据库中的数据进行归约，并将归约后的数据作为训练数据提供给BP神经网络；再用遗传算法和BP算法相结合的混合算法来训练网络预测模型的结构（在得到最优网络结构的同时也得到网络的最优权值和阈值）。通过实例表明该方法是有效的，为环境质量评价提供了一种新的研究思路和分析方法。