Fuzzy Complex Index in Water Quality Assessment of Municipalities

Donghu Lake in Wuhan is a multipurpose complex water body. However, its eutrophication phenomenon becomes increasingly serious. By making use of detailed and accurate contamination monitoring data and several mathematics models, we probe into the dynamic state of water quality. The year’s average value of major contamination index in Donghu Lake from 2001 to 2008 and fuzzy complex index are used to assess its short-term state of water quality. The results show that its water quality is basically stable in the 4th class of water quality standard GB3838-2002.

AN ANALYSIS OF THE APPLICABILITY OF FUZZY CLUSTERING IN ESTABLISHING AN INDEX FOR THE EVALUATION OF METEOROLOGICAL SERVICE SATISFACTION

An evaluation index is a prerequisite for the scientific evaluation of a public meteorological service.This paper aims to explore a technical method for determining and screening evaluation indicators.Based on public satisfaction survey data obtained in Wafangdian,China in 2010,this study investigates the suitability of fuzzy clustering analysis method in establishing an evaluation index.Through quantitative analysis of multilayer fuzzy clustering of various evaluation indicators,correlation analysis indicates that if the results of clustering were identical for two evaluation indicators in the same sub-evaluation layer,then one indicator could be removed,or the two indicators merged.For evaluation indicators in different sub-evaluation layers,although clustering reveals attribute correlations,these indicators may not be substituted for one another.Analysis of the applicability of the fuzzy clustering method shows that it plays a certain role in the establishment and correction of an evaluation index.

A NEW TECHNIQUE FOR COMPAIRING FUZZY NUMBERS USING AN INDEX OF OPTIMISM

Fuzzy numbers are convenient for representing imprecise numerical quantities in a vague environment, and their comparison or ranking is very important for application purposes. Despite many methods suggested in the literature, there is no single measure that is universally applicable to a wide variety of situations. This paper suggested a new method for comparing fuzzy numbers based on the combination of maximizing possibility and minimizing possibility using an index of optimism in [0,1] reflecting the decision makers’ risk taking attitude. The method is simple, but has many comparative advantages.

Kind of Fuzzy Method Determining Index Weight on Multi-Objctive Decision Making

Based on fuzzy characteristic of dicision-making thought, matrix of priority relation has been introduced and blurrized. A kind of fuzzy method, which is to determine the index weight on multi-objective decision making, has been put forward by means of the sequence root method for analysis of hierarchical process (AHP). Using this method an example which is to define the index weigbt on multi-objective decision making in thc scheme optimization of mine design has been given.

Genetic Algorithms of Structural Fuzzy Reliability Index

In this paper the simple generation algorithms are improved. According to the geometric meaning of the structural reliability index, a method is proposed to deal with the variables in the standard normal space. With consideration of variable distribution, the correlation coefficient of the variables and its fuzzy reliability index, the feasibility and the reliability of the algorithms are proved with an example of structural reliability analysis and optimization.

Spectral purification improves monitoring accuracy of the comprehensive growth evaluation index for film-mulched winter wheat

In order to further improve the utility of unmanned aerial vehicle(UAV)remote-sensing for quickly and accurately monitoring the growth of winter wheat under film mulching, this study examined the treatments of ridge mulching,ridge–furrow full mulching, and flat cropping full mulching in winter wheat.Based on the fuzzy comprehensive evaluation (FCE) method, four agronomic parameters (leaf area index, above-ground biomass, plant height, and leaf chlorophyll content) were used to calculate the comprehensive growth evaluation index (CGEI) of the winter wheat, and 14 visible and near-infrared spectral indices were calculated using spectral purification technology to process the remote-sensing image data of winter wheat obtained by multispectral UAV.Four machine learning algorithms, partial least squares, support vector machines, random forests, and artificial neural network networks(ANN), were used to build the winter wheat growth monitoring model under film mulching, and accuracy evaluation and mapping of the spatial and temporal distribution of winter wheat growth status were carried out.The results showed that the CGEI of winter wheat under film mulching constructed using the FCE method could objectively and comprehensively evaluate the crop growth status.The accuracy of remote-sensing inversion of the CGEI based on the ANN model was higher than for the individual agronomic parameters, with a coefficient of determination of 0.75,a root mean square error of 8.40, and a mean absolute value error of 6.53.Spectral purification could eliminate the interference of background effects caused by mulching and soil, effectively improving the accuracy of the remotesensing inversion of winter wheat under film mulching, with the best inversion effect achieved on the ridge–furrow full mulching area after spectral purification.The results of this study provide a theoretical reference for the use of UAV remote-sensing to monitor the growth status of winter wheat with film mulching.

Applications of fuzzy similarity index method in processing of hypnosis

The brain is a highly complex system. Under-standing the behavior and dynamics of billions of interconnected neurons from the brain signal requires knowledge of several signal- process-ing techniques, from the linear and non-linear domains. The analysis of EEG signals plays an important role in a wide range of applications, such as psychotropic drug research, sleep studies, seizure detection and hypnosis proc-essing. In this paper we accomplish to analyze and explore the nature of hypnosis in Right, Left, Back and Frontal hemisphere in 3 groups of hypnotizable subjects by means of Fuzzy Simi-larity Index method.

STUDY OF APPLICATION OF FUZZY SYNTHETICAL JUDGMENT IN CLASSIFYING THE LOWING INDEX OF BLOOD

Flowing index of blood reports the features of 'concentration, viscoelasticity, polymerization, coacervation' of blood. It is impportant in diagnosing of cerebral blood vessel disease. Thispaper uses the method of fuzzy synthetical judgment firstly to classify the flowing index of bloodautomaticaly. A new fuzzy subordinary function is introduced and the single factor evaluation matrix is formed based on it. The invalidity of fuzzy synthetical judgment is discussed also, and approach is given when the judgment is invalid. Finally, we give an example to demonstrate theusefulness and advantages of our method.

Prediction of the undrained shear strength of remolded soil with non-linear regression,fuzzy logic,and artificial neural network

This study aims to predict the undrained shear strength of remolded soil samples using non-linear regression analyses,fuzzy logic,and artificial neural network modeling.A total of 1306 undrained shear strength results from 230 different remolded soil test settings reported in 21 publications were collected,utilizing six different measurement devices.Although water content,plastic limit,and liquid limit were used as input parameters for fuzzy logic and artificial neural network modeling,liquidity index or water content ratio was considered as an input parameter for non-linear regression analyses.In non-linear regression analyses,12 different regression equations were derived for the prediction of undrained shear strength of remolded soil.Feed-Forward backpropagation and the TANSIG transfer function were used for artificial neural network modeling,while the Mamdani inference system was preferred with trapezoidal and triangular membership functions for fuzzy logic modeling.The experimental results of 914 tests were used for training of the artificial neural network models,196 for validation and 196 for testing.It was observed that the accuracy of the artificial neural network and fuzzy logic modeling was higher than that of the non-linear regression analyses.Furthermore,a simple and reliable regression equation was proposed for assessments of undrained shear strength values with higher coefficients of determination.

AHP-FUZZY综合评判方法在绿色供应链评价中的应用

目的构建AHP-FUZZY(层次分析-模糊综合评判)模型对绿色供应链的客户、财务、学习与发展、业务流程、绿色环保等指标进行评判,探索综合评判模型在绿色供应链评价中应用的可行性.方法在利用绿色供应链概念的基础上建立绿色供应链综合评价指标体系,借助层次分析法构建判断矩阵,确定各级指标权重并进行一致性检验,并由权重集和模糊评判矩阵构建模糊综合评判模型对整个绿色供应链及各指标进行评价.结果通过实例验证分析,所构建的绿色供应链指标评价体系具有科学性和适用性,AHP-FUZZY综合评判方法在绿色供应链的综合评价中具有合理性和可行性.该绿色供应链的综合评价考核得分为86.69,处于良好和优秀之间,说明整个供应链的运行基本满足预期目标,但尚有提升空间.结论评价结果表明,AHP-FUZZY综合评判模型能够客观的评价绿色供应链的效果并为绿色供应链的最佳调控提供理论支持,并有效指导绿色供应链的评价、分析、调整、决策等工作.

基于属性权重的Fuzzy C Mean算法

提出CF-WFCM算法,该算法分为属性权重学习算法和聚类算法两部分.属性权重学习算法,从数据自身的相似性出发,通过梯度递减算法极小化属性评价函数CFuzziness(w),为每个属性赋予一个权重.将属性权重应用于Fuzzy C Mean聚类算法,得到CF-WFCM算法的聚类算法.CF-WFCM算法强化重要属性在聚类过程中的作用,消减冗余属性的作用,从而改善聚类的效果.我们选取了部分UCI数据库进行实验,实验结果证明:CF-WFCM算法的聚类结果优于FCM算法的聚类结果.函数CFuzziness(w)不仅可以评价属性的重要性,而且可以评价属性评价函数的优劣.实验说明了这一问题.最后我们对CF-WFCM算法进行了讨论.

基于Fuzzy AHP的主题公园游客满意度综合评价

游客满意度是旅游景观、基础设施和景区管理等多因素综合评价的心理反映,是景区游客流的基本动力.本文在分析主题公园游客满意度影响因素的基础上,探索并提炼影响游客满意度的主要因素,构建主题公园游客满意度的测评指标体系.此外,传统游客满意度测量尺度多为离散型数值,如采用"4→5"描述"满意→非常满意"状态的变化,忽略了游客感知的连续性,因此本文采用连续性三角数值,如"(50,75,100)→(75,100,100)"描述"满意→非常满意"状态变化,结合模糊综合评价法,建立其测评体系的数学模型,客观、准确地评价主题公园游客满意度,为景区管理者提供决策的辅助工具.

基于虚拟水理论与Fuzzy-AHP方法的区域水安全评价研究

从社会经济安全、粮食安全、水资源与生态安全3个方面构建了由13个指标组成的区域水安全的指标体系,结合虚拟水理论对部分指标进行量化,采用Fuzzy-AHP方法,以郑州市为例,对其1998-2005年及2015和2020年在丰、平、枯3个水文年下的水安全状况进行评价。结果表明,人均水足迹、人均水资源量、粮食安全指数、依赖指数、粮食自给度、水资源压力指数6个指标权重之和占总权重的79%,该6个方面决定着区域水安全状况;郑州市的综合评价结果为区域综合安全状况、社会经济安全层、粮食安全层为安全,资源生态安全层为较安全,表明郑州市经济社会和粮食安全是以牺牲区域资源和生态安全为代价的,所以郑州市区域水安全状况是一种结构不合理的安全状况。

小麦面粉指标关系中的Fuzzy非线性回归问题

小麦面粉指标关系大都呈现一定的模糊性.利用Fuzzy结构元理论对小麦面粉指标中的模糊关系进行了分析,给出了一种处理模糊非线性关系的Fuzzy非线性回归模型,实例表明模型适用,既为处理模糊关系提供了一种新方法,也为小麦面粉的综合研究提供参考.

AHP—Fuzzy在无水港发展潜力评价中的应用

通过分析无水港的空间结构及发展模式,选取影响无水港发展的7大因素,构建无水港发展潜力评价指标体系,运用层次分析法(AHP)和多层模糊(Multi-Level Fuzzy)综合评判相结合的模型评价福建泉州晋江无水港发展潜力。实证结果表明:该项目发展水平良好,发展潜力较大,物流业发展水平、地区经济环境与无水港执行效率表现较为突出,制约其发展的主要因素是交通基础设施。

城市地下空间综合效益评价的一种新方法——模糊(Fuzzy Set)评价模型

如何正确地评价城市地下空间综合效益是一个具有现实意义的课题。为了寻求城市地下空间综合效益评价方法及结果的统一性和实用性,本文针对综合评价指标中所出现的大量模糊性,在建立恰当的隶属函数基础上,对软、硬指标进行二级模糊评价运算,提出了一种较为符合实际的综合效益评价方法——模糊(Fuzzy Set)评价模型,并能在计算机上快速操作得出定量化评价结果。最后,本文还以沿海某大城市的已建人防工程综合效益评价作为考评对象,对模型的实际应用进行了验证。

AHP-Fuzzy数学模型在尘肺综合防治效果评价指标体系中的应用

尘肺病是我国目前最严重的职业病,而实施尘肺防治效果评价是做好尘肺综合防治工作关口前移的基本前提。本研究根据现场调研、文献调查、理论分析、专家咨询并结合现场工程技术人员意见,确定了尘肺防治效果综合评价主要影响因素,建立起了尘肺防治效果综合评价的指标体系。采用AHP-Fuzzy数学模型对企业尘肺防治效果的综合评价。并将该模型应用于实际的煤矿尘肺综合防治中,得出客观的评价结论,从而验证了评价模型的实用性。

基于AHP-FUZZY的教学评价系统的设计与应用

教学质量评价本身是一个典型的不确定性问题。为了科学合理地检验高校的教育质量,结合所在学校的教学评价指标体系,依据教学领域督学专家的知识和经验,提出了基于AHP-FUZZY的教学质量评价系统的设计方案。首先,运用层次分析法(AHP)合理地确定了评价指标的权重;其次运用模糊决策将定量分析还原成评价等级,进行综合评价;最后根据实际需求开发了教学质量评价系统。该系统应用于实际的教学质量评价中,能够对教学质量进行准确、高效的评价,为教学质量评价的研究提供了有意义的参考价值。

Fuzzy-AHP在LNG接收站风险辨识中的应用

笔者以液化天然气(LNG)接受站的生产工艺、设备、作业环境的特点为背景,提出一种基于模糊层次分析方法(Fuzzy-Analytic Hierarchy Process)的风险评估方法。首先,根据LNG接收站风险事故多层次、多因素及不确定的特点,结合本行业的安全标准,确立了LNG接受站的风险因素和评价指标,建立接受站的安全评价体系;随后,运用Fuzzy-AHP方法确定权重矢量和模糊评价矩阵,并通过模糊运算求出决策矢量,实现对风险因素的排序以达到风险辨识目的;最后,对国内某LNG站进行了实例计算。计算表明该接收站的硬件设施完善,但应加强风险管理,制定相应的措施应对因气候条件、储罐区管理不当及船舶安全保护不到位等引发的事故。结果表明基于LNG站的Fuzzy-AHP风险辨识模型的安全性综合评价是有效的。