基于GIS的略阳县地质环境质量评价

基于地理信息系统(GIS)和多级模糊模式识别模型,建立了略阳县空间数据库和地质环境质量评价模型;综合考虑地形坡度、工程地质岩组、岩土体结构类型、地下水位、植被发育情况、月平均降雨量、人类工程活动强度等因素,用层次分析法确定各指标权值,应用评价模型对略阳县地质环境质量进行了综合评价,把略阳县地质环境划分为优、良、中、差4个质量级别。     

基于模糊集的数量属性关联规则方法的研究

根据模糊集原理,提出了一种数量型数据挖掘关联规则的方法,并通过试验证明了算法的合理性.     

The strategy of building a flood forecast model by neuro‐fuzzy network

A methodology is proposed for constructing a flood forecast model using the adaptive neuro‐fuzzy inference system (ANFIS). This is based on a self‐organizing rule‐base generator, a feedforward network, and fuzzy control arithmetic. Given the rainfall‐runoff patterns, ANFIS could systematically and effectively construct flood forecast models. The precipitation and flow data sets of the Choshui River in central Taiwan are analysed to identify the useful input variables and then the forecasting model can be self‐constructed through ANFIS. The analysis results suggest that the persistent effect and upstream flow information are the key effects for modelling the flood forecast, and the watershed's average rainfall provides further information and enhances the accuracy of the model performance. For the purpose of comparison, the commonly used back‐propagation neural network (BPNN) is also examined. The forecast results demonstrate that ANFIS is superior to the BPNN, and ANFIS can effectively and reliably construct an accurate flood forecast model. Copyright © 2005 John Wiley & Sons, Ltd.     

River suspended sediment modelling using a fuzzy logic approach

Correct estimation of sediment volume carried by a river is very important for many water resources projects. Conventional sediment rating curves, however, are not able to provide sufficiently accurate results. In this paper, a fuzzy logic approach is proposed to estimate suspended sediment concentration from streamflow. This study provides forecasting benchmarks for sediment concentration prediction in the form of a numerical and graphical comparison between fuzzy and rating‐curve models. Benchmarking was based on a 5‐year period of continuous streamflow and sediment concentration data of Quebrada Blanca Station operated by the United States Geological Survey. The benchmark results showed that the fuzzy model was able to produce much better results than rating‐curve models. The fuzzy model proposed in the study is site specific and does not simulate the hysteresis effects. Copyright © 2006 John Wiley & Sons, Ltd.     

Counterpropagation fuzzy–neural network for streamflow reconstruction

This study combines neural networks and fuzzy arithmetic to present a counterpropagation fuzzy–neural network (CFNN) for streamflow reconstruction. The CFNN has a rule‐based control, a modified self‐organizing counterpropagation network, and a fuzzy control predictor. It can generate rules automatically by increasing the training data to improve the accuracy of streamflow reconstruction. The CFNN establishes the input and output relationship of a watershed without set‐up parameters. The parameters are estimated systematically by the approach converging to an optimal solution. One sequence of data generated by the Monte Carlo method is used to demonstrate the accuracy of the CFNN. The streamflow data of the Da‐chia River, in central Taiwan, is also used to evaluate the performances of the CFNN. The results indicate the reliability and accuracy of the CFNN for streamflow reconstruction. Copyright © 2001 John Wiley & Sons, Ltd.     

模糊综合评判法在济源城区水质污染程度评价中的应用

本文用模糊数学方法对河南济源城区地下水水质污染程度进行了综合评价。文中以三个标准和四个级别、线段函数和折线法作为确定隶属函数的基础,然后采用统一基本权重和具体样本附加权重相组合并经归一化处理而求得实际权重。继之,选用“∨·∧”、“×·+”两种模型的算子进行综合评判。整个评判过程均在微机上实现。评判结果清楚地反映出了该地区的污染程度。文中,笔者结合该区自然条件及水文地质条件,分析了各种级别水的成因,并对该区今后的污染治理提出了指导性的意见。     

基于X波段双偏振雷达的贵州威宁一次冰雹过程水成物粒子识别研究

利用贵州威宁雪山X波段双偏振天气雷达一次冰雹过程观测资料,基于MATLAB软件对雷达观测数据进行数据质量控制基础上利用模糊逻辑算法对冰雹云中水成物粒子进行识别分类,主要结论如下：（1）采用综合小波去噪能够有效去除差分传播相位（ФDP）存才的脉动和毛刺,保证ФDP的连续性和平滑度,保留有效ФDP值,其用于雷达反射率因子衰减订正具有较好的效果。（2）冰雹形成与低密度霰（LDG）、高密度霰（HDG）以及过冷水（SCW）的增减演变较为对应,霰粒子是冰雹形成的关键粒子。（3）从霰粒子出现到识别出冰雹时间为26 min,约4个体扫时间,从识别出冰雹到地面观测到降雹32 min,约5个体扫时间。（4）冰雹识别结果与地面观测总体一致,所构建的识别参量阈值基本合理,研究所构建的粒子相态识别方法在贵州威宁具有普适性,可为冰雹早起识别、预警和人工防雹作业提供技术和理论支撑。     

WorldView-2影像与OLI影像协同岩性模糊分类

Landsat系列、ASTER等中等空间分辨率遥感数据（中分数据）覆盖了碳酸盐矿物、粘土矿物、铁氧化物矿物等矿物的诊断光谱区间,广泛应用于矿物、岩石信息提取,但受限于空间分辨率,混合像元现象明显,严重制约了其岩性分类精度。WorldView-2、QuickBird等高空间分辨率遥感数据（高分数据）提供了岩石地层表面丰富的空间结构信息,同时空间分辨率的提高也是缓解混合像元效应的最有效途径,但高分数据覆盖的光谱区间往往较窄,难以满足大多数特征吸收谱段位于短波红外、热红外区间的矿物、岩石信息提取。在岩性自动分类方法上,前人研究中仍以采用基于像元的分类方法为主,分类结果的“椒盐现象（Salt-and-pepper,出现在分类结果图中大量孤立的错分点或小图斑）”严重。为结合中分数据的光谱信息优势和高分数据的空间结构信息优势,同时减少基于像元的岩性分类方法中的“椒盐现象”,提高岩性自动分类精度,本文以Landsat 8 OLI数据和WorldView-2数据为例,提出了一种协同中、高分遥感数据进行面向对象的岩性模糊分类的方法。首先通过“结构协同”和“光谱协同”方案对WorldView-2数据和OLI数据进行信息协同,利用主成分变换对协同后数据的纹理信息和光谱信息进行压缩和增强,然后将增强后的纹理信息和光谱信息进行波段绑定,并进行多尺度分割。根据岩性单元间的光谱特征和纹理特征的差异,构建各岩性单元的模糊逻辑隶属度函数,实现对研究区岩性的模糊分类。实验结果表明,该方法成功划分了岩性单元的分布,总体岩性分类精度为89.35％。     

基于模糊集重心的DLG产品质量的模糊综合评判

DLG产品作为GIS的一种重要数字产品形式,其数据质量是保证系统可靠性、有效性的关键.本文对影响DLG产品质量因素进行了详细分析,在此基础上,将基于模糊重心综合评判应用于DLG产品的质量评估,较好地解决了传统模糊综合评判的信息丢失问题,使评估方法更加有效、可行.     

基于模糊理论的智能最优路径算法

在经典Dijkstra算法原理的基础上,提出基于模糊理论的智能最优路径算法.该算法综合考虑静态交通信息、动态交通信息和人的主观因素等路径选择的影响因素,建立路径选取度模型,确定影响因素的隶属度函数.该方法能够根据用户出行的不同目的和需求,自动调整各影响因素之间的权重,从而使路径选择既能满足用户的主观要求,又能真实反映复...