Assessing Suitability of Rural Settlements Using an Improved Technique for Order Preference by Similarity to Ideal Solution

Land suitability assessment is a prerequisite phase in land use planning; it guides toward optimal land use by providing information on the opportunities and constraints involved in the use of a given land area. A geographic information system-based procedure, known as rural settlement suitability evaluation(RSSE) using an improved technique for order preference by similarity to ideal solution(TOPSIS), was adopted to determine the most suitable area for constructing rural settlements in different geographical locations. Given the distribution and independence of rural settlements, a distinctive evaluation criteria system that differed from that of urban suitability was established by considering the level of rural infrastructure services as well as living and working conditions. The unpredictable mutual interference among evaluation factors has been found in practical works. An improved TOPSIS using Mahalanobis distance was applied to solve the unpredictable correlation among the criteria in a suitability evaluation. Uncertainty and sensitivity analyses obtained via Monte Carlo simulation were performed to examine the robustness of the model. Daye, a resource-based city with rapid economic development, unsatisfied rural development, and geological environmental problems caused by mining, was used as a case study. Results indicate the following findings: 1) The RSSE model using the improved TOPSIS can assess the suitability of rural settlements, and the suitability maps generated using the improved TOPSIS have higher information density than those generated using traditional TOPSIS. The robustness of the model is improved, and the uncertainty is reduced in the suitability results. 2) Highly suitable land is mainly distributed in the northeast of the study area, and the majority of which is cultivated land, thereby leading to tremendous pressure on the loss of cultivated land. 3) Lastly, 12.54% of the constructive expansion permitted zone and 8.36% of the constructive expansion conditionally permitted zone are situated in an unsuitable area, which indicates that the general planning of Daye lacks the necessary verification of suitability evaluation. Guidance is provided on the development strategy of rural settlement patches to support decision making in general land use planning.

Research on Network Maintenance Strategy Selection Based on Analytic Hierarchy Process and Technique for Order Preference by Similarity to Ideal Solution Algorithm

Network maintenance strategy selection is a multi-objective decision making topic. It mostly depends on the uncertainty and fuzziness of decision makers and conditions. In this paper, based on analytic hierarchy process(AHP) and technique for order preference by similarity to ideal solution(TOPSIS), TOPSIS partial order method is proposed to choose the optimal maintenance strategy. This method uses AHP to determine the weights of evaluation indexes. The optimal maintenance strategy choice is given as an example to demonstrate the effectiveness of the method.

基于云-TOPSIS法的应急物流供应商综合评价

为实现应急物流降本增效的目标,从供应商层面出发,运用云-逼近理想解排序法(TOPSIS)评价应急物流供应商综合能力;根据应急物流特点,从应急响应能力、物资质量、成本控制、应急响应柔性、企业内外部条件等5方面,构建应急物流供应商综合评价指标体系;借鉴博弈论思想,将用改进熵权法求得的客观权重和用层次分析法(AHP)求得的主观权重作为博弈对手,确定最优组合权重;运用云模型量化指标决策云和加权云对供应商的模糊定性评价语义;采用TOPSIS法构建正负理想解集合,计算备选方案与正负理想解的距离确定相对贴近度,确定最优备选方案。研究结果表明:指标决策云能准确地将评价语言量化,云-TOPSIS法的评价结果更合理;在供应商相对贴近度排序中,采用云-TOPSIS法计算的最优与最劣者差值为0.3315,而TOPSIS法为0.0882,两者相差0.2433,表明云-TOPSIS法的评价结果区分度更大,能更直观地辅助决策者做出最优选择。

基于TOPSIS法和波士顿矩阵的医院神经专科能力评估研究

目的通过对以神经科学集群建设为特色的三级甲等医院的神经专科能力进行评估,为国内医院的特色专科建设提供参考。方法从服务能力、技术能力、质量安全和服务效率4个维度建立神经外科、神经内科专科能力评估指标体系,通过优劣解距离(technique for order preference by similarity to ideal solution,TOPSIS)法纵向比较首都医科大学附属北京天坛医院神经专科2019—2023年发展趋势,并采用波士顿矩阵深入分析神经专科各亚专业建设情况。结果2019—2023年首都医科大学附属北京天坛医院神经专科TOPSIS综合得分指数呈上升趋势。神经外科以胶质瘤诊治为主的肿瘤专业1,在技术能力和质量安全方面得分指数最高;神经内科以脑血管病为主的亚专业,在技术能力和服务效率方面得分指数较高,以上两个亚专业在波士顿矩阵中均处于优势巩固区。结论2019—2023年首都医科大学附属北京天坛医院神经专科诊治能力不断提升。神经外科亚专业中,专科能力排名最高的为肿瘤专业1,诊疗技术难度较高,同时医疗质量负性事件发生率低。神经内科各亚专业中,脑血管专业诊疗技术难度高且服务高效。

一测多评法测定法制半夏曲中11种成分含量及其GRA、EW-TOPSIS质量评价

目的采用一测多评(QAMS)法同时测定法制半夏曲中肌苷、鸟苷、腺苷等11种成分含量,并建立其灰色关联度分析(GRA)联合熵权逼近理想解排序分析法(EW-TOPSIS)综合质量评价方法。方法采用Shimadzu C 18色谱柱;乙腈-0.5%醋酸为流动相,梯度洗脱,流速1.0 mL·min-1;检测波长254和290 nm。以对甲氧基肉桂酸乙酯为内参比物质,计算其他10个成分的相对校正因子(RCF),测定各成分含量。采用GRA联合EW-TOPSIS模型对法制半夏曲进行综合质量评价。结果法制半夏曲中11种成分在一定浓度范围内线性关系良好,相关系数均>0.999;平均加样回收率96.94%~100.12%(RSD<2.0%,n=9);QAMS与外标法(ESM)实测值无明显差异。GRA模型相对关联度0.2903~0.6187,EW-TOPSIS模型相对接近度0.2114~0.6343;GRA和EW-TOPSIS模型综合评价结果基本一致。结论QAMS法便捷、准确,可用于法制半夏曲多指标成分定量控制,GRA联合EW-TOPSIS模型可用于法制半夏曲综合质量评价。

基于TOPSIS和GRA的信息安全风险评估

信息安全风险评估是一项非常重要的信息安全保障活动.依据信息安全相关标准,可从资产、威胁和脆弱性3方面识别出重要的风险因素,并确定相应的信息安全风险评估指标.参考等保2.0确定风险评估指标是一种可行的方法.在进行信息安全风险评估时,采用熵权法进行客观的指标赋权,并结合优劣解距离法(technique for order preference by similarity to ideal solution,TOPSIS)和灰色关联分析(grey relational analysis,GRA)进行综合评估.实例分析表明,依据信息熵进行客观赋权相对减少了主观因素的影响;基于TOPSIS和GRA进行信息安全风险评估,综合被评价对象整体因素和内部因素,较有效地将多项信息安全风险评估指标综合成单一评分,便于对多个被评对象进行信息安全风险的择优与排序.

Extension of TOPSIS for fuzzy multi-attribute decision making problem based on experimental analysis

This paper is concerned with a technique for order performance by similarity to ideal solution（TOPSIS） method for fuzzy multi-attribute decision making,in which the information about attribute weights is partly known and the attribute values take form of triangular fuzzy numbers.Considering the fact that the triangular fuzzy TOPSIS results yielded by different distance measures are different from others,a comparative analysis of triangular fuzzy TOPSIS ranking from each distance measure is illustrated with discussion on standard deviation.By applying the most reasonable distance,the deviation degrees between attribute values are measured.A linear programming model based on the maximal deviation of weighted attribute values is established to obtain the attribute weights.Therefore,alternatives are ranked by using TOPSIS method.Finally,a numerical example is given to show the feasibility and effectiveness of the method.

Ranking approach of cross-efficiency based on improved TOPSIS technique

The cross-efficiency evaluation method is reviewed which is developed as a data envelopment analysis （DEA） extensive tool. The cross-efficiency evaluation method is utilized to identify the decision making unit （DMU） with the best practice and to rank the DMUs by their respective cross-efficiency scores. The main drawbacks of the cross-efficiency evaluation method when the ultimate average cross-efficiency scores are used to evalu- ate and rank the DMUs are also pointed out. With the research gap, an improved technique for order preference by similarity to ideal solution （TOPSIS） is introduced to rank the crossfficiency by eliminating the average assumption. Finally, an empirical example is illustrated to examine the validity of the proposed method.

Threat evaluation method of warships formation air defense based on AR(p)-DITOPSIS

For the target threat evaluation of warships formation air defense, the sample data are frequently insufficient and even incomplete. The existing evaluation methods rely too much on expertise and are difficult to carry out for the dynamic evaluation on time series. In order to solve these problems, a threat evaluation method based on the AR(p)(auto regressive(AR))-dynamic improved technique for order preference by similarity to ideal solution(DITOPSIS) method is proposed. The AR(p) model is adopted to predict the missing data on the time series. Then, the entropy weight method is applied to solve each index weight at the objective point. Kullback-Leibler divergence(KLD) is used to improve the traditional TOPSIS, and to carry out the target threat evaluation. The Poisson distribution is used to assign the weight value.Simulation results show that the improved AR(p)-DITOPSIS threat evaluation method can synthetically take into account the target threat degree in time series and is more suitable for the threat evaluation under the condition of missing the target data than the traditional TOPSIS method.

Combining TOPSIS and GRA for supplier selection problem with interval numbers

Supplier selection can be regarded as a typical multiple attribute decision-making problem. In real-world situation, the values of the alternative attributes and their weights are always being nondeterministic, and as a result of this, the values are considered interval numbers. In addition, the common approach to measure the similarity between alternatives through their distance suffers from some minor shortcomings. To address these problems, this study develops a novel hybrid decision-making method by combining the technique for order preference by similarity to an ideal solution （TOPSIS） with grey relational analysis （GRA） for supplier selection with interval numbers. By introducing the intervals theory, the extensions of Euclidean distance and grey relational grade are defined. And then a new comprehensive closeness coefficient is constituted for supplier alternatives evaluation based on the interval Euclidean distance and the interval grey relational grade, which could indicate the distance-based similarity and the shape-based similarity simultaneously. A mtmerical example is taken to validate the flexibility of the proposed method, and result shows that this method can tackle the uncertainty in real-world supplier selection and also help decision makers to effectively select optimal suppliers.

Weakness Ranking Method for Subsystems of Heavy-Duty Machine Tools Based on FMECA Information

Heavy-duty machine tools are composed of many subsystems with different functions,and their reliability is governed by the reliabilities of these subsystems.It is important to rank the weaknesses of subsystems and identify the weakest subsystem to optimize products and improve their reliabilities.However,traditional ranking methods based on failure mode effect and critical analysis(FMECA)does not consider the complex maintenance of products.Herein,a weakness ranking method for the subsystems of heavy-duty machine tools is proposed based on generalized FMECA information.In this method,eight reliability indexes,including maintainability and maintenance cost,are considered in the generalized FMECA information.Subsequently,the cognition best worst method is used to calculate the weight of each screened index,and the weaknesses of the subsystems are ranked using a technique for order preference by similarity to an ideal solution.Finally,based on the failure data collected from certain domestic heavy-duty horizontal lathes,the weakness ranking result of the subsystems is obtained to verify the effectiveness of the proposed method.An improved weakness ranking method that can comprehensively analyze and identify weak subsystems is proposed herein for designing and improving the reliability of complex electromechanical products.

基于AHP与TOPSIS的水电站能效管理水平评价方法研究

针对现有水电站能效管理水平评价方法的不足,将层次分析法(AHP)和优劣解距离法(TOPSIS)引入评价过程中,综合考虑经济、安全和管理3个方面的因素,构建了水电站能效管理评价指标体系;针对九分位标度法的不足,采用指数标度法确定各指标权重;分别利用TOPSIS方法和专家打分法对定量指标、定性指标进行评分,并进一步实现水电站能效管理水平的综合评价;以某实际水电站为例,分析和计算2018-2022年的水电站能效管理水平得分,结果表明该电站能效管理水平总体上呈上升趋势。

A Decision Support System for Selection of Solar Power Plant Locations by Applying Fuzzy AHP and TOPSIS: An Empirical Study

The objective of this research is to propose a decision support system for avoiding flood on solar power plant site selection. Methodologically, the geographic information system (GIS) is used to determine the optimum site for a solar power plant. It is intended to integrate the qualitative and quantitative variables based upon the adoption of the Fuzzy Analytic Hierarchy Process (Fuzzy AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) model. These methods are employed to unite the environmental aspects and social needs for electrical power systematically. Regarding a case study of the choice of a solar power plant site in Thailand, it demonstrates that the quantitative and qualitative criteria should be realized prior to analysis in the Fuzzy AHP-TOPSIS model. The fuzzy AHP is employed to determine the weights of qualitative and quantitative criteria that can affect the selection process. The adoption of the fuzzy AHP is aimed to model the linguistic unclear, ambiguous, and incomplete knowledge. Additionally, TOPSIS, which is a ranking multi-criteria decision making method, is employed to rank the alternative sites based upon overall efficiency. The contribution of this paper lies in the evolution of a new approach that is flexible and practical to the decision maker, in providing the guidelines for the solar power plant site choices under stakeholder needs: at the same time, the desirable functions are achieved, in avoiding flood, reducing cost, time and causing less environmental impact. The new approach is assessed in the empirical study during major flooding in Thailand during the fourth quarter of 2011 to 2012. The result analysis and sensitivity analysis are also presented.

DNA extraction method selection for agricultural soil using TOPSIS multiple criteria decision-making model

There is an increased interest in the extraction of nucleic acids from various environmental samples since culture-independent molecular techniques contribute to deepen and broaden the understanding of a greater portion of uncultivable microorganisms. Due to difficulties to select the optimum DNA extraction method in view of downstream molecular analyses, this article presents a straightforward mathematical framework for comparing some of the most commonly used methods. Four commercial DNA extraction kits and two physical-chemical methods (bead-beating and freeze-thaw) were compared for the extraction of DNA under several quantitative DNA analysis criteria: yield of extraction, purity of extracted DNA (A260/280 and A260/230 ratios), degradation degree of DNA, easiness of PCR amplification, duration of extraction, and cost per extraction. From a practical point of view, it is unlikely that a single DNA extraction strategy can be optimum for all selected criteria. Hence, a systematic Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was employed to compare the methods. The PowerSoil? DNA Isolation Kit was systematically defined as the best performing method for extracting DNA from soil samples. More specifically, for soil:manure and soil:manure:biochar mixtures, the PowerSoil?DNA Isolation Kit method performed best, while for neat soil samples its alternative version gained the first rank.

基于AHP和TOPSIS-模糊综合评价的多场景储能选型方法

目前储能技术路线多样,不同类型的储能各具应用前景,但储能选型需要综合考虑经济性、安全性等因素,是一个复杂的多目标决策问题,因此储能选型是工程应用中的关键问题之一。提出一种将层次分析法(analytic hierarchy process,AHP)和优劣解距离法(technique for order preference by similarity to ideal solution,TOPSIS)-模糊综合分析法相结合的储能选型评价体系。首先,通过建立评价体系的判断矩阵,利用AHP获取指标权重;其次,将判断矩阵里量纲不同的指标类型用TOPSIS做规范化处理,以此获得更客观的权重向量,改善AHP法的主观性;而后,将指标权重对角化处理并与标准化后的矩阵相乘获得加权判断矩阵,并求取贴近度向量。最后,加权判断矩阵与模糊综合分析法关系矩阵相乘获取储能类型的隶属度评价结果,并以隶属度最大值所在的等级为最终评价,处于等级Ⅰ中最佳,等级Ⅱ次之并以此类推;由此通过TOPSIS获得更客观的权重向量,改善AHP法的主观性,得到的权重向量也更客观。最后以锂离子电池、钠硫电池和铅酸电池等七种储能类型在应用于削峰填谷、电网保供电和改善电压质量场景为例,并与现有的储能选型方法进行比较,体现该评价体系的创新,检验所提评价体系和选型方法的有效性。

Optimal design of functionally graded Pm PV/CNT nanocomposite cylindrical tube for purpose of torque transmission

Carbon nanotube(CNT)/polymer nanocomposites have vast application in industry because of their light mass and high strength. In this work, a cylindrical tube which is made up of functionally graded(FG) PmP V/CNT nanocomposite, is optimally designed for the purpose of torque transmission. The main confining parameters of a rotating shaft in torque transmission process are mass of the shaft, critical speed of rotation and critical buckling torque. It is required to solve a multi-objective optimization problem(MOP) to consider these three targets simultaneously in the process of design. The three-objective optimization problem for this case is defined and solved using a hybrid method of FEM and modified non-dominated sorting genetic algorithm(NSGA-II), by coupling two softwares, MATLAB and ABAQUS. Optimization process provides a set of non-dominated optimal design vectors. Then, two methods, nearest to ideal point(NIP) and technique for ordering preferences by similarity to ideal solution(TOPSIS), are employed to choose trade-off optimum design vectors. Optimum parameters that are obtained from this work are compared with the results of previous studies for similar cylindrical tubes made from composite or a hybrid of aluminum and composite that more than 20% improvement is observed in all of the objective functions.

TOPSIS with Belief Structure for Group Belief Multiple Criteria Decision Making

The technique for order performance by similarity to ideal solution （TOPSIS） is one of the major techniques in dealing with multiple criteria decision making （MCDM） problems, and the belief structure （BS） model has been used successfully for uncertain MCDM with incompleteness, impreciseness or ignorance. In this paper, the TOPSIS method with BS model is proposed to solve group belief MCDM problems. Firstly, the group belief MCDM problem is structured as a belief decision matrix in which the judgments of each decision maker are described as BS models, and then the evidential reasoning approach is used for aggregating the multiple decision makers＇ judgments. Subsequently, the positive and negative ideal belief solutions are defined with the principle of TOPSIS. To measure the separation from ideal solutions, the concept and algorithm of belief distance measure are defined, which can be used for comparing the difference between BS models. Finally, the relative closeness and ranking index are calculated for ranking the alternatives. A numerical example is given to illustrate the proposed method.

Fuzzy TOPSIS method to primary crusher selection for Golegohar Iron Mine(Iran)

Selection of the crusher required a great deal of design regarding to the mine planning. Selection of suitable primary crusher from all of available primary crushers is a multi-criterion decision making(MCDM) problem. The present work explores the use of technique for order performance by similarity to ideal solution(TOPSIS) with fuzzy set theory to select best primary crusher for Golegohar Iron Mine in Iran. Gyratory, double toggle jaw, single toggle jaw, high speed roll crusher, low speed sizer, impact crusher, hammer mill and feeder breaker crushers have been considered as alternatives. Also, the capacity, feed size, product size, rock compressive strength, abrasion index and application of primary crusher for mobile plants were considered as criteria for solution of this MCDM problem. To determine the order of the alternatives, closeness coefficient is defined by calculating the distances to the fuzzy positive ideal solution(FPIS) and fuzzy negative ideal solution(FNIS). Results of our work based on fuzzy TOPSIS method show that the gyratory is the best primary crusher for the studied mine.

基于熵权TOPSIS法综合评价应用PDCA法管控抗菌药物的成效——以某三甲医院为例

目的 探讨某三甲医院构建抗菌药物科学化管理策略与实施成效,为医疗机构加强抗菌药物管理提供参考依据。方法 使用计划、执行、检查、处理(PDCA)管理工具,构建科学有效的抗菌药物管理系统,选取抗菌药物管理相关5个维度、14个指标构建质量评价考核体系,并采用熵权逼近理想解排序法(TOPSIS)法对实施PDCA改进后各项指标的变化情况进行综合评价与分析。结果 基于熵权TOPSIS法分析,2018年的相对接近度(Ci)值为0.313 5,该年抗菌药物管理质量最低;2022年的Ci值为0.747 4,该年抗菌药物管理质量最高。抗菌药物合理使用5个维度方面,使用强度维度2017年Ci值最高;使用率维度2021年Ci值最高;送检率维度2022年Ci值最高;Ⅰ类切口预防用药维度2022年Ci值最高;住院患者抗菌药物费用维度2022年Ci值最高。应用PDCA法进行抗菌药物管理,管理质量整体呈现改善趋势。结论 基于PDCA法通过多部门协作进行抗菌药物管理干预效果显著,熵权TOPSIS法可用于评价抗菌药物管理成效,为医院抗菌药物管控方向指导及政策制定提供参考。

基于梯度模糊TOPSIS导弹目标的威胁评估

针对导弹目标威胁评估问题,提出了一种基于梯度模糊的TOPSIS导弹目标威胁评估算法。利用TOPSIS方法计算权重值并结合梯度模糊计算的模糊矩阵,得到目标威胁评估指标的综合权重值,可解决各因素数据指标量级差异过大而引起的权重值偏差过大或过小等问题。典型案例评估结果表明,所提改进算法克服了权重值差异性问题,有效提升了导弹目标威胁评估的可信性。