Ranking Method for Complementary Judgment Matrixes with Fuzzy Numbers Based on Hausdorff Metric Distance

A method for ranking complementary judgment matrixes with traspezoidal fuzzy numbers based on Hausdorff metric distance and fuzzy compromise decision approach is proposed. With regard to fuzzy number complementary judgment matrixes given by a decider group whose members have various weights, the expert＇s information was aggregated first by means of simple weight average（SWA） method and Bonissone calculational method. Hence a matrix including all the experts＇ preference information was got. Then the matrix＇ column members were added up and the fuzzy evaluation values of the alternatives were got. Lastly, the Hausdorff metric distance and fuzzy compromise decision approach were used to rank the fuzzy evaluation values and then the ranking values of all the alternatives were got. Because exact numbers and triangular fuzzy numbers could all be transformed into trapezoidal fuzzy numbers, the method developed can rank complementary judgment matrixes with trapezoidal fuzzy numbers, triangular fuzzy numbers and exact numbers as well. An illustrative example is also given to verify the developed method and to demonstrate its feasibility and practicality.

Multi-level fuzzy comprehensive appraisal on social effects of projects

The application of multi-level fuzzy comprehensive appraisal on social effects of projects has been studied. The principles for setting up an index system have been analyzed and the index system has been set up according to projects of construction. Models for multi-level fuzzy comprehensive appraisal have been offered and relative calculation steps have been given according to project instances.

Fuzzy Comprehensive Judgment on the Mechanical Equipment Bid Sheet

The reasonable model of fuzzy comprehensive judgment is found by means of the theory and method of multi-level fuzzy judgment on the basis of the judging index system of mechanical equipment bid sheets. The scientific method is supplied for the judging bids, the key chain of the judging process of the mechanical equipment bid sheet. All factors are considered, especially quantitative factors or qualitative factors in the process of judgment.

Air Target Fuzzy Pattern Recognition Threat-Judgment Model

Threat-judgment is a complicated fuzzy inference problem. Up to now no relevant unified theory and measur-ing standard have been developed. It is very difficult to establish a threat-judgment model with high reliability in the airdefense system for the naval warships. Air target threat level judgment is an important component in naval warship com-bat command decision-making systems. According to the threat level judgment of air targets during the air defense of sin-gle naval warship, a fuzzy pattern recognition model for judging the threat from air targets is established. Then an algo-rithm for identifying the parameters in the model is presented. The model has an adaptive feature and can dynamicallyupdate its parameters according to the state change of the attacking targets and the environment. The method presentedhere can be used for the air defense system threat judgment in the naval warships.

Tank Fire Control Systems Accuracy Assignment Based on Fuzzy Comprehensive Judgment Method

A method of accuracy assignment based on fuzzy comprehensive judgment method (FCJM) in tank fire control system is proposed. From the flowing route of the error sources and their respective correlative signals, the transfer functions of several sources are analysed by means of mathematic simulation, and FCJM is applied to obtain the cost comprehensive factor for each part of system, combining its error sensitivity factor the mathematical model is built to solve the accuracy assignment problem. Simulation result shows the proposed method can help designer of tank fire control system work out an optimal system more efficiently and more economically.

Neural Network Based Multi-level Fuzzy Evaluation Model for Mechanical Kinematic Scheme

To implement a quantificational evaluation for mechanical kinematic scheme more effectively,a multi-level and multi-objective evaluation model is presented using neural network and fuzzy theory. Firstly,the structure of evaluation model is constructed according to evaluation indicator system. Then evaluation samples are generated and provided to train this model. Thus it can reflect the relation between attributive value and evaluation result,as well as the weight of evaluation indicator. Once evaluation indicators of each candidate are fuzzily quantified and fed into the trained network model,the corresponding evaluation result is outputted and the best alternative can be selected. Under this model,expert knowledge can be effectively acquired and expressed,and the quantificational evaluation can be implemented for kinematic scheme with multi-level evaluation indicator system. Several key problems on this model are discussed and an illustration has demonstrated that this model is feasible and can be regarded as a new idea for solving kinematic scheme evaluation.

Obtaining Crisp Priorities for Triangular and Trapezoidal Fuzzy Judgments

This paper proposes anoptimal fuzzy-based model for obtaining crisp priorities for Fuzzy-AHP comparison matrices.Crisp judgments cannot be given for real-life situations,as most of these include some level of fuzziness and com-plexity.In these situations,judgments are represented by the set of fuzzy numbers.Most of the fuzzy optimization models derive crisp priorities for judgments repre-sented with Triangular Fuzzy Numbers(TFNs)only.They do not work for other types of Triangular Shaped Fuzzy Numbers(TSFNs)and Trapezoidal Fuzzy Numbers(TrFNs).To overcome this problem,a sum of squared error(SSE)based optimization model is proposed.Unlike some other methods,the proposed model derives crisp weights from all of the above-mentioned fuzzy judgments.A fuzzy number is simulated using the Monte Carlo method.A threshold-based constraint is also applied to minimize the deviation from the initial judgments.Genetic Algorithm(GA)is used to solve the optimization model.We have also conducted casestudiesto show the proposed approach’s advantages over the existingmethods.Results show that the proposed model outperforms other models to minimize SSE and deviation from initial judgments.Thus,the proposed model can be applied in various real time scenarios as it can reduce the SSE value upto 29%compared to the existing studies.

Assessment of Effects of Green Construction by Analytic Hierarchy Process and Fuzzy Synthetic Judgment Method

The index system, code system, and weights of indexes are established to assess the effects of green construction. The index system consists of index level, factor level and sub-factor level. The analytic hierarchy process is used to determine the weights of indexes, and the consistency test indicate that the weight assignment is reasonable. Using fuzzy synthetic judgment method, the assessment model is built, which includes factor set, weight set and conclusion set. An example is given to demonstrate the assessment procedures.

Research on Power Consumption Anomaly Detection Based on Fuzzy Clustering and Trend Judgment

Among the end-users of the power grid,especially in the rural power grid,there are a large number of users and the situation is complex.In this complex situation,there are more leakage caused by insulation damage and a small number of users stealing electricity.Maintenance staff will take a long time to determine the location of the abnormal user meter box.In view of this situation,themethod of subjective fuzzy clustering and quartile difference is adopted to determine the partition threshold.The power consumption data of end-users are divided into three regions:high,normal and low,which can be used to screen users in the area of abnormal power consumption.Then the trend judgment method is used to further accurately screen to improve the accuracy and reduce the number of users in the abnormal range.Finally according to abnormal power consumption auxiliary locate abnormal electricity users list box.Then the simulation environment is set to verify the application of membership fuzzy clustering and trend judgment in power consumption data partition.

Multi-Level Fuzzy Comprehensive Assessment of Tourism Resources in Laiyuan County of Hebei Province

The membership of every target and the mathematic model of multi-level fuzzy comprehensive assessment are set up by using fuzzy theories and means in this study.Tourism resources of main scenic spots areas in Laiyuan County of Hebei Province are evaluated and classified by applying the model.The results of evaluation indicate that 10 of these scenic spots such as Baoziwo and Qingyunfeng are grade A,and 6 of them such as Yunpan Valley and Xianrenqiao are grade B.The peak forest scenic area in the Baishishan Geological Park and Shipuxia Scenic Area are grade A,and Jumayuan Scenic Area is grade B.Furthermore,suggestions are put forward based on the scientific and feasible development of tourism resources.

Fuzzy pattern recognition model of geological sweetspot for coalbed methane development

From the perspective of geological zone selection for coalbed methane(CBM) development, the evaluation parameters(covering geological conditions and production conditions) of geological sweetspot for CBM development are determined, and the evaluation index system of geological sweetspot for CBM development is established. On this basis, the fuzzy pattern recognition(FPR) model of geological sweetspot for CBM development is built. The model is applied to evaluate four units of No.3 Coal Seam in the Fanzhuang Block, southern Qinshui Basin, China. The evaluation results are consistent with the actual development effect and the existing research results, which verifies the rationality and reliability of the FPR model. The research shows that the proposed FPR model of geological sweetspot for CBM development does not involve parameter weighting which leads to uncertainties in the results of the conventional models such as analytic hierarchy process and multi-level fuzzy synthesis judgment, and features a simple computation without the construction of multi-level judgment matrix. The FPR model provides reliable results to support the efficient development of CBM.

Fuzzy-Bayes Decision Making with Reserved Judgement

This paper discusses a method for identifying states in a multistage Decision Making Problem in which an Indifferent Event is either predetermined or can be automatically derived after the fact. First, when they are pre-set, the amount of possible information about Indifferent Event tends to be large. Therefore, since the decision is risk tolerant, the Max-Product method of Tanaka et al. is used to calculate the expected utility possibility. Next, in the case of automatic derivation after the fact, the amount of information on the possibility of Indifferent Event is relatively small, so the expected utility possibility is derived using Zadeh’s Fuzzy Event Possibility Measure. Here, it is assumed that the setting of the utility function is independent of the information on the occurrence of the Indifferent Event and is identified by the decision maker by lot drawing using the certainty equivalence method. As a concrete example, we focus on the pass/fail decision of a recommendation test, which is a two choice question in the No-Data Problem, and illustrate the multistage state identification method. .

乘型模糊判断矩阵排序向量的递推方法

文章首先在模糊判断矩阵乘型一致性以及矩阵元素和权重之间关系的基础上,结合模糊判断矩阵的上三角矩阵元素,构建了一个关于权重和矩阵上三角元素的方程组,并证明了该方程组存在唯一的正解。随后指出方程组的证明过程就是模糊判断矩阵排序向量的求解过程,从而给出了乘型一致性模糊判断矩阵排序向量的一种递推方法。然后,在偏差函数基础上,通过构造并求解一个优化模型,求出了非乘型一致性模糊判断矩阵的排序向量,结果显示,其解的形式与采用乘型一致性模糊判断矩阵递推方法得到的排序向量完全一样。最后,通过实例以及相关方法对比说明排序向量递推方法是可行有效的。

基于模糊综合评判和本体的测量仪器智能优选研究

针对当前测量仪器的种类逐渐增多且各仪器都有不同的性能影响因素问题,提出了一种基于模糊综合评判和本体的测量仪器智能优选研究。首先,利用模糊综合评判对测量仪器的性能影响因素进行模糊划分;其次,依据本体领域知识,将模糊划分模型转化为测量仪器智能优选的本体模型,运用SWRL规则和protégé工具推理出最优的测量仪器;最后,通过工程实例展示该方法的工作过程,验证了该方法的可行性。实验结果表明,提出的方法可以为仪器选择提供参考,并可自动推理结果。

基于模糊评判理论的简支梁桥安全性评估

根据某简支梁桥的外观检测数据和无损检测数据,运用模糊评判理论对该桥进行评定,外观检测数据和无损检测数据评定结果表明该桥技术状况总体良好。

群组Fuzzy判断矩阵集结方法及其一致性

基于Fuzzy判断矩阵一致性的定义,提出一种构造一致性Fuzzy判断矩阵的新方法,建立了一种加权集结方法的最优化模型,从而得到了群组决策中一类Fuzzy判断矩阵的集结方法,并进一步对其一致性进行了分析和研究。理论分析表明,该集结方法在群组决策中具有明确的实际意义。

基于Fuzzy判断矩阵的一致性调整方法

基于模糊判断矩阵完全一致性的定义,给出一种调整模糊判断矩阵一致性的新方法。首先,讨论了衡量判断矩阵一致性程度的指标,从而给出了满意一致性的判定方法,然后提出了构造完全一致性模糊判断矩阵的变换公式,通过分析反映完全一致性矩阵和初始判断矩阵之间关系的偏差矩阵,得到一种新的一致性调整算法,最后进行算例分析。

基于Fuzzy模型的矿井通风系统风流稳定性评判

针对矿井通风系统具有复杂、多变、随机等内涵明确、外延模糊的特点,在研究其稳定性相关基础上应用Fuzzy数学的方法对诸多因素进行综合判定。根据矿井通风系统风流稳定性所涉及的范围,本着科学、可测、可操作的原则建立了评价指标集合,采用了层次分析法确定权重,通过根据调查划分出不同评判等级并给出了Fuzzy判定模型和解算方法,为分级管理提供了科学依据,为正确指导现场生产打下基础。

川滇地区工程场外道路地震风险评估研究

水利水电工程场外道路的地震风险判定,对工程项目实施进度起着重要作用。本文中以川滇地区工程场外道路为研究对象,采用模糊集合理论和判断矩阵法,建立地质环境和地震危险性两大因子破坏的综合评估数学模型,分析37个地州市遭受地震后道路破坏情况的可能性。分析表明:川滇地区工程场外道路遭受地震中等破坏的可能性较大,且位于四川的工程场外道路遭受到地震风险破坏的指数高于云南地区的地震风险评估值。