Application of Fuzzy Comprehensive Evaluation Method Based on Entropy Weight Theory in Evaluation of Salt Tolerance of Cotton

[Objective] The aim was to propose a new entropy weight fuzzy compre- hensive evaluation method for assessing cotton salt tolerance, realizing the objective, accurate and comprehensive evaluation of salt tolerance of cotton. [Method] A sand culture experiment under salt stress of 150 mmol/L of NaCI was designed. The in- dicator weight was determined with the entropy weight fuzzy comprehensive evalu- ation method, based on the salt injury index of indicators. The salt tolerance of cotton was evaluated comprehensively. [Result] At the germination stage, the entropy and weight of salt injury index of germination energy, vigor index, hypocotyl length and fresh weight were highest, followed by germination rate and germination index, and of root length were lowest. At the seedling stage, the entropy and weight of salt injury index of plasma membrane permeability, root vigor and leaf expansion rate were highest, followed by plant height and net photosynthetic rate, and of shoot dry weight and root dry weight were lowest. The salt tolerance of cotton differed a- mong growth stages and cultivars. Among the 11 cultivars, CCRI-44 and CCRI-75 were steadily salt-tolerant at both germination and seedling stages; CCRI-17, Sumi- an 22, Sumian 15 and Dexiamianl had a stable moderate salt tolerance; while Sumian 12 and Simian 3 were steadily salt-sensitive. [Conclusion] The evaluated result was objective and exact, which indicated that this method could be used in comprehensive evaluation of salt tolerance of cotton.

Application of Fuzzy Comprehensive Evaluation Method Based on Entropy Weight to Evaluate Pond Water Quality

[Objective] This study was to provide references for the evaluation of water quality in aquaculture ponds by evaluating the pond water quality using fuzzy comprehensive evaluation method based on entropy weight. [Method] The fuzzy compre- hensive evaluation method based on entropy weight was used to evaluate the water quality in the ponds with Ukraine scale carp （Cyprinus carpio） as the main cultivated fish. The average size of the fish was 71.4 g/ind, and totally three groups of pond were set with the population density of 6 000, 9 000, 12 000 ind/hm2. [Result] According to the GB3838-2002 Environmental Quality Standards for Surface Water of China, the water quality of 6 000 ind/hm2 group was Grade I, and the water quality of 9 000 and 12 000 ind/hm2 were Grade V. [Conclusion] With the increasing of feeding density, the pond water quality would worsen, however, there is no difference on water quality between 9 000 and 12 000 ind/hm2 groups.

多场景下基于AHP-EWM的人体健康状态评估模型研究

为解决人体健康评估方法个性化监测不足的问题以及在满足不同场景下健康状态精细化评估的需求,需要一种基于多场景的人体健康状态评估方法来实现长期自动化监测。提出一种基于层次分析法(AHP)和熵权法(EWM)组合的多场景人体健康状态评估模型。首先采集人体在运动、休息、工作/学习和娱乐等4种不同场景下的健康监测指标数据,构建相应的评估指标体系。然后分别根据评估指标计算出AHP和EWM权重,再采用量子粒子群优化(QPSO)算法对AHP和EWM中的主客观权重进行分配,以确保评价指标占比的客观性。最后通过模糊综合评价法对人体健康状态进行评估和量化,并利用实际监测数据对方法的可靠性和稳定性进行验证。实验结果表明,在4种场景下所提方法的综合得分分别为63.78、59.83、58.71和59.21,表明在不同场景下该模型都具有较好的准确性和稳定性。根据评估结果,对测试者的身体状态评价结果进行分析,并给出一些健康建议。所提模型可全面了解人体在不同场景下的健康状况,并为人们提供科学的健康指导,从而为健康管理和疾病预防提供科学依据。

Entropy method for determination of weight of evaluating indicators in fuzzy synthetic evaluation for water quality assessment

Considering the difficulty of fuzzy synthetic evaluation method in calculation of the multiple factors and ignorance of the relationship among evaluating objects, a new weight evaluation process using entropy method was introduced. This improved method for determination of weight of the evaluating indicators was applied in water quality assessment of the Three Gorges reservoir area. The results showed that this method was favorable for fuzzy synthetic evaluation when there were more than one evaluating objects. One calculation was enough for calculating every monitoring point. Compared with the original evaluation method, the method predigested the fuzzy synthetic evaluation process greatly and the evaluation results are more reasonable.

Identifying influential spreaders in complex networks based on entropy weight method and gravity law

In complex networks,identifying influential spreader is of great significance for improving the reliability of networks and ensuring the safe and effective operation of networks.Nowadays,it is widely used in power networks,aviation networks,computer networks,and social networks,and so on.Traditional centrality methods mainly include degree centrality,closeness centrality,betweenness centrality,eigenvector centrality,k-shell,etc.However,single centrality method is onesided and inaccurate,and sometimes many nodes have the same centrality value,namely the same ranking result,which makes it difficult to distinguish between nodes.According to several classical methods of identifying influential nodes,in this paper we propose a novel method that is more full-scaled and universally applicable.Taken into account in this method are several aspects of node’s properties,including local topological characteristics,central location of nodes,propagation characteristics,and properties of neighbor nodes.In view of the idea of the multi-attribute decision-making,we regard the basic centrality method as node’s attribute and use the entropy weight method to weigh different attributes,and obtain node’s combined centrality.Then,the combined centrality is applied to the gravity law to comprehensively identify influential nodes in networks.Finally,the classical susceptible-infected-recovered(SIR)model is used to simulate the epidemic spreading in six real-society networks.Our proposed method not only considers the four topological properties of nodes,but also emphasizes the influence of neighbor nodes from the aspect of gravity.It is proved that the new method can effectively overcome the disadvantages of single centrality method and increase the accuracy of identifying influential nodes,which is of great significance for monitoring and controlling the complex networks.

An Information Entropy-Based Methodology to Construct the Avulsion Threshold in the Tail Reach of the Estuarine Alluvial Plain

Channel avulsion is a natural phenomenon that occurs abruptly on alluvial river deltas,which can affect the channel stability.The causes for avulsion could be generally categorized as topography-and flood-driven factors.However,previous studies on avulsion thresholds usually focused on topography-driven factors due to the centurial or millennial avulsion timescales of the world’s most deltas,but neglected the impacts of flood-driven factors.In the current study,a novel demarcation equation including the two driven factors was proposed,with the decadal timescale of avulsion being considered in the Yellow River Estuary(YRE).In order to quantify the contributions of different factors in each category,an entropy-based methodology was used to calculate the contributing weights of these factors.The factor with the highest weight in each category was then used to construct the demarcation equation,based on avulsion datasets associated with the YRE.An avulsion threshold was deduced according to the demarcation equation.This avulsion threshold was then applied to conduct the risk assessment of avulsion in the YRE.The results show that:two dominant factors cover respectively geomorphic coefficient representing the topography-driven factor and fluvial erosion intensity representing the flood-driven factor,which were thus employed to define a two dimensional mathematical space in which the demarcation equation can be obtained;the avulsion threshold derived from the equation was also applied in the risk assessment of avulsion;and the avulsion threshold proposed in this study is more accurate,as compared with the existing thresholds.

Weight Determining of Factors Influencing Grain Output Based on Entropy Weight Method

This article selects 8 main factors(the number of rural employees,total power of agricultural machinery,effective irrigation area of crops,growing area of grain crops,fertilizer consumption,electricity consumption in rural areas,area affected and area covered) as the factors influencing grain output,and offers the method of determining weight of factors influencing grain output using entropy weight method.According to the relevant data in the period 1985-2005,we analyze the weight of factors influencing grain output in China by example.The results show that the electricity consumption in rural areas has the greatest impact on grain output,followed by total power of agricultural machinery,fertilizer consumption and area covered.To increase grain output,we must enhance the degree of mechanization,free people from the former process of direct cultivation,strengthen water conservancy construction,and do a good job in disaster prevention and mitigation.

基于改进SPA-EWM理论的隧道通风竖井掘进风险评估模型

为满足“一次成深大竖井”的高效成井要求,竖井掘进机(shaft boring machine,SBM)应需而生。以竖井掘进机的工程应用为研究背景,分析和辨识了竖井掘进机掘进的风险因素,将竖井施工风险划分成5个等级,并构建了三层级的竖井掘进风险评估指标体系。考虑联系度中同、异、反的取值问题,将集对分析理论(set-pair analysis,SPA)中的联系度赋值方法进行了有效改进,同时结合熵权法(entropy weight method,EWM)计算各风险因素的联系度表达式,建立了一种改进集对分析理论的深地竖井SBM掘进风险评估模型,并对联系度与风险计算值的变化关系进行趋势拟合,从而给出风险水平评估依据。借助该风险评估模型,对沿江高速火山隧道通风竖井进行了施工风险评估及预测,提出了风险偏好不同的工程人员对竖井掘进风险的不同取值方法,结合现场布测结果进一步验证了风险模型的适用性。立足我国SBM工法的初次应用,提出的深地竖井SBM掘进风险评估模型为深大竖井施工起到了一定指导作用,也为今后深地竖井掘进的风险评估研究奠定了一定理论基础。

基于BWM-EWM的铁路综合客运枢纽站城融合发展水平评价研究

铁路综合客运枢纽站城融合发展已经成为城市高质量发展的重要催化剂,亟需科学决策铁路综合客运枢纽站城融合的开发规模和力度。通过铁路综合客运枢纽站城融合评价指标体系评价原则构建,从交通发展水平、土地利用水平和站城衔接水平3个准则层,提出铁路综合客运枢纽站城融合评价指标体系,建立基于BWM-EWM的铁路综合客运枢纽站城融合发展水平评价模型。以北京南站、上海虹桥站、南京南站、深圳北站和重庆沙坪坝站5个典型铁路综合客运枢纽进行实证分析,研究结果表明:南京南站具有较好的站城融合水平,还需要进一步强化枢纽统筹协调、提高站城衔接水平,集中开发枢纽用地、提高土地开发效益。

基于FAHP-EWM-TOPSIS的新型电力负荷管理系统的通信方式适配方法

针对目前新型电力负荷管理系统的发展,文章旨在寻找一种合适的通信方式来承载系统端到端的通信。首先,从新型电力负荷管理系统的概念出发,剖析差异化业务需求,建立业务指标体系架构;其次,基于模糊层次分析法-熵权法-逼近理想解排序法,分析最优通信方式的选择策略;最后通过算例,分析不同通信方式对差异化业务的适配程度,确定符合新型电力负荷管理系统的最优通信方式,为新型电力负荷管理系统通信架构搭建提出参考性意见。

基于AHP-EWM权重与模糊评判的风机齿轮箱健康评价方法

针对传统故障诊断算法依据人工经验判断、对数据挖掘不深等问题,提出使用模糊评判T1FL法将齿轮箱系统的综合评价划分为4个健康状态。为了科学地赋权各级状态指标所占的健康权重,构建以最小二乘法耦合改进的层次分析法(AHP)和改进的熵权法NBN-EWM的数字化权重计算模型。结果表明:所提方法以多源数据为输入,通过最大隶属度原则综合评估齿轮箱的健康状态,诊断出齿轮箱部件高速轴处存在0.9201的置信空间为齿轮断齿状态,对4种健康状态的评估准确率分别保持在99%、99.2%、98.2%与99.6%。所提方法能够应用于齿轮箱的早期故障诊断,量化评判齿轮箱部件的健康状态,精确定位齿轮箱的损伤部位,为机组运维策略提供安全性保障,并为风场的能源数字化、设备智能健康与运维提供新方案。

基于IAHP-EWM博弈论的煤层底板突水影响因素研究

为了研究影响底板突水的水文地质和管理因素,利用文献调研法确立了6个一级指标和20个二级指标的层次分析模型;收集8例突水事故指标数据,根据事故发生经过和事故原因分析,采用1~9标度体现人员管理因素指标对事故发生概率和后果的影响程度;利用区间层次分析法(IAHP)和熵权法(EWM)对所收集数据进行分析,利用博弈论对所确立指标进行组合赋权。研究结果表明,水文地质因素方面隔水层厚度和含水层水压权重最高,在管理因素方面地质基础资料不足是影响突水的关键因素,通过与其他类似研究对比,指标权重计算排序结果具有一定合理性,为研究底板突水提供方法参考,为煤层底板突水的精确防治和管理提供借鉴。

基于AHP-EWM-模糊综合评价的智能油库成熟度评价

随着物联网、大数据等技术的发展,石化行业正朝着智能化的方向迈进。作为储存石油产品的重要场所,油库的智能化发展相对缓慢。为提升油库的智能化水平、促进油库的智能化发展,基于中国国内油库智能化现状,从生产运行管理、环保安全管理、巡检设备管理等三大业务维度,建立了智能油库成熟度评价模型,将层次分析法和熵权法相结合,得出智能油库成熟度模型的各指标权重,并通过模糊综合评价分析评估智能油库的得分情况,进一步得出智能油库的成熟度等级。最后,以某油库为例进行了智能油库成熟度的评价分析,根据最终成熟度等级评估结果分析了该油库关键业务的不足,提出了针对性的改进优化措施,以期提升其整体智能化水平。

基于IAHP-EWM-FCE的矿山救护队应急救援能力评价

矿山应急救援队伍是煤矿企业应急能力建设工作中必不可少的一部分。针对矿山应急救援能力评价指标选取的模糊性和不规范性,采用模糊综合评价法(FCE)对矿山救护队应急救援能力进行评价。首先,根据应急救援队伍相关法律标准、文献研究、专家咨询等方式确定矿山救护队应急救援能力评价指标,构建相应的评价指标体系;然后,通过改进层次分析法(IAHP)和熵权法(EWM)进行矿山应急救援能力评价指标权重确定;最后,引入模糊综合评价法,对某矿山救护队应急救援能力进行综合评价,为煤矿应急能力建设提供理论支撑。实证分析表明,所构建的矿山救护队能力评价模型能够全面、准确地评估出某矿山救护队应急救援能力等级,有助于提升矿山救护队应急救援能力,从而加强煤矿企业应急能力建设。

Study on Entropy Weight Coefficient Method and Application for Water Quality Evaluation

In order to evaluate the quality of water environment, the conception of entropy is applied in information science, and the entropy weight model is built to evaluate comprehensively water quality. The indexes weights of water quality are determined by value of entropy. This kind of method is applied on evaluating water quality in the new water to be built. The result shows that the water quality in it which supply water is between grade Ⅲ and Ⅳ, and the result is similar to that of gray related method.

基于EAHP-EWM-博弈TOPSIS的大坝风险 识别方法

针对大坝风险指标具有不确定性和模糊性的特征,提出了1种基于EAHP-EWM-博弈TOPSIS组合模型的大坝风险识别模型,即通过可拓层次分析法和熵权法分别确定风险评价指标的主、客观权重,同时引入博弈理论确定最佳组合权重,并构造加权标准化决策矩阵,然后利用TOPSIS法计算出各风险因子与理想解的相对接近度作为风险因子排序的依据来识别大坝的主要风险源,最后将该方法应用于福建省某大坝的风险识别。工程实例表明,影响该大坝安全服役的主要风险因子为坝体渗流与两岸渗流,相对接近度分别为0.7127、0.8552,识别的主要风险因子和工程实际情况相吻合,验证了模型的有效性。本模型的区分度相比其他模型更明显,为大坝的除险加固和风险管理提供了有效依据。

基于EWM-GRA综合评价的采场结构参数优化研究

为实现某地下磷矿增产目标,在综合考虑采矿安全、技术和经济因素下,结合EWM熵权法和GRA灰关联度法构建了EWM-GRA综合评价模型,并基于评价模型对9组不同采场结构参数方案进行分析。研究结果表明:选择采用进路宽度为3.5 m,进路高度为3 m的方案最优。从现场实践来看,采用3.5m×3m采场结构参数方案相对原方案采矿量每米整体提高了27.37%,可实现增产目标;每条进路的经济效益相对原方案增加了2.833万元,大于增加的开采成本,说明了优选出的采场结构参数方案是合理可行的。研究结果可为磷矿采场结构参数设计提供参考。

Evaluation Model of Rural Drinking Water Project Based on Entropy Weight and Fuzzy Comprehensive Evaluation Method

Based on Measures for Assessment of Rural Drinking Water Standard Raising Action in Zhejiang Province,this study established an evaluation system for rural drinking water project in Zhejiang Province,covering three primary indicators of project construction,project management and project performance,and 18 secondary indicators.It proposed an evaluation model based on entropy weight and fuzzy evaluation method.It solved the problems of the objectivity of the indicator weight and the quantification of the indicators,and can well achieve the coordination and unity of fuzziness and accuracy.Using this model,it evaluated a rural drinking water project in a county and concluded that both accuracy and feasibility of the model are high.

基于FAHP-Entropy赋权法的矿山地质环境影响评价:以武鸣区灰岩矿山为例

矿山地质环境影响评价是一个兼具复杂性和模糊性的系统,是将有限的修复资源如何合理地分配到不同影响程度矿山的科学依据。为了更精准、更高效地评价矿山对周边地质环境的影响状况及程度,本文选择南宁市武鸣区38个灰岩矿山为研究对象,从地质环境背景、资源破坏、地质灾害、矿山开发利用状况4个方面选取了14个评价指标构建矿山地质环境影响评价体系,采用模糊层次分析法和熵值法相结合(FAHP-Entropy组合)赋权法综合评价矿山地质环境影响程度,并基于MATLAB平台开发了矿山地质环境影响评价系统(MGES),对38座灰岩矿山进行评价。评价结果显示,对地质环境影响较轻的矿山仅占比21%,对地质环境影响较严重的矿山占比47%,对地质环境影响严重的矿山占比32%,武鸣区矿山地质环境影响程度整体属较严重~严重级别。研究结果为武鸣区政府有限的治理资金指明了优先治理方向。该系统操作简单,可以弥补传统方法复杂、难操作的不足之处,对于处理大规模数据有极大优势,可为同业技术人员和学者开展矿山地质环境影响评价工作提供借鉴。

Comprehensive Evaluation of New Fresh Edible Sweet-glutinous Maize Varieties Based on Entropy Weight Method

In this study,the entropy weight method was used to comprehensively evaluate the eight sweet-glutinous maize varieties in the regional trials in Shanxi Province in 2016. The results showed that the order of the performance of comprehensive traits of the tested varieties was Heitiannuo 631,Heitiannuo No. 2,Cainuo No. 5,Xinnuo 8601,FYN 1601,Xinnuo 8608,Jindannuo 41,Caitiannuo 1958( from good to poor). Among them,Heitiannuo 631,Heitiannuo No. 2 and Cainuo No. 5 are excellent varieties,and the rest are good varieties.