Fuzzy Judgment Research Articles

Research on Function Determination Method of Aviation Equipment Spare Part Demands under Small Samples

Acquaintance of fault distribution rules of aviation material spare parts is one of the important measures to conduct scientific management of aviation materials, while data collection is the basis to determine the aviation material fault function. The paper proposes suggestions for collection methods and collection opportunities of fault data of aviation material spare parts. Aiming at the actual situation that the same group of data could easily satisfy multiple distributions under small samples and based on a judgment model with combination of improved fuzzy judgment and improved AHP method, a rational distribution function was obtained with expert experience as reference. Through the research on determination of the spare part demand function in the paper, a foundation was laid for supply, reserve and computation of aviation materials. In this way, aviation material demands could be predicted accurate, and economy of aviation equipment guarantee could be enhanced.

РАЗРАБОТКА МЕТОДА ОЦЕНКИ СОСТОЯНИЯ БАЗОВЫХ СТАНЦИЙ ДЛЯ ОПРЕДЕЛЕНИЯ НЕОБХОДИМОСТИ ИХ МОДЕРНИЗАЦИИ

The article consideres the problems of determining the need to modernize the base stations of the cellular network based on the mathematical apparatus of the theory of fuzzy sets. To improve the quality of telecommunications services the operators should send significant funding for upgrading the equipment of base stations. Modernization can improve and extend the functions of base stations to provide cellular communication, increase the reliability of the base station in operation and the functionality of its individual elements, and reduce the cost of maintenance and repair when working on a cellular network. The complexity in collecting information about the equipment condition is determined by a large number of factors that affect its operation, as well as the imperfection of obtaining and processing the information received. For a comprehensive assessment of the need for modernization, it is necessary to take into account a number of indicators. In the structure of indicators of the need for modernization, there were introduced the parameters reflecting both the degree of aging and obsolescence(the technical gap and the backlog in connection with the emergence of new technologies and standards). In the process of a problem solving, the basic stages of decision-making on modernization have been allocated. Decision-making on the need for modernization is based not only on measuring information that takes into account the decision-makers, but also on linguistic and verbal information. Therefore, to determine the need for upgrading the base stations, the theory of fuzzy sets is used, with the help of which experts can be attracted to this issue. They will be able to formulate additional fuzzy judgments that help to take into account not only measuring characteristics, but also poorly formalized fuzzy information. To do this, the main indicators of the modernization need have been defined, and fuzzy estimates of the need for modernization for all indicators and a set of indicators reflecting the need for upgrading the base stations have been formulated.

A decision-making model based on interval additive reciprocal matrices with additive approximation-consistency

In order to capture the rationality experienced by decision makers in choosing the best alternative(s), of much interest is to study the consistency of preference relations in the analytic hierarchy process (AHP). When the typical AHP is extended by using fuzzy numbers to evaluate the opinions of decision makers, the consistency of fuzzy judgments is worth to be considered. In this paper, we analyze some definitions of interval additive reciprocal matrices with additive consistency. It is concluded that interval additive reciprocal matrices are inconsistent in essence. The concept of additive approximation-consistency of interval additive reciprocal matrices is proposed. Moreover, a novel exchange method is designed to enumerate all permutations of alternatives for checking the approximation-consistency. By considering the randomness exhibited in pairwisely comparing alternatives, a method of obtaining the interval weight vector is given. A new algorithm of solving the decision making problem with interval additive reciprocal matrices is proposed. Finally, two numerical examples are carried out to illustrate the new definition and some comparisons are offered.

An integrated logarithmic fuzzy preference programming based methodology for optimum maintenance strategies selection

Selecting optimum maintenance strategies plays a key role in saving cost, and improving the system reliability and availability. Analytic hierarchical process (AHP) is widely used for maintenance strategies selection in the Multiple Criteria Decision-Making (MCDM) field. But the traditional or hybrid AHP methods either produce multiple, even conflict priority results, or have complicated algorithm structures which are unstable to obtain the optimum solution. Therefore, this paper proposes an integrated Logarithmic Fuzzy Preference Programming (LFPP) based methodology in AHP to solve the optimum maintenance strategies selection problem. The multiplicative constraints and deviation variables are applied instead of additive ones to utilize both qualitative and quantitative data, and process the upper and lower triangular fuzzy judgments to obtain the same priorities. The proposed methodology can produce the unique normalized optimal priority vector for fuzzy pairwise comparison matrices, and it is capable of processing all comparison matrices to obtain the global priorities simultaneously and directly in the form of super-matrix according to the different requirements and judgments of decision-makers. Finally, an example is provided to demonstrate the feasibility and validity of the proposed methodology.

Acceptability measurement and priority weight elicitation of triangular fuzzy multiplicative preference relations based on geometric consistency and uncertainty indices

This paper investigates consistency and uncertainty measurements as well as acceptability checking for triangular fuzzy multiplicative preference relations (TFMPRs). A geometric consistency index is proposed to measure the consistency degree of a TFMPR, and thresholds of acceptable consistency are discussed for TFMPRs. Uncertainty indices are introduced to measure indeterminacy degrees of triangular fuzzy judgments and of TFMPRs and a notion of acceptable TFMPRs are put forward by considering both acceptable consistency and acceptable uncertainty in TFMPRs. We also explore the elicitation of triangular fuzzy weights from acceptable TFMPRs and the aggregation of local triangular fuzzy weights for solving hierarchical multi-criteria decision-making problems. A geometric mean-based equation and a logarithmic least square model are developed to elicit normalized acceptable triangular fuzzy multiplicative weights from an acceptable TFMPR. An equation and a linear program are established to transform triangular fuzzy multiplicative weights into triangular fuzzy additive weights. A geometric weighting-based equation and a pair of linear programs are devised to generate global priority fuzzy weights from local triangular fuzzy multiplicative weights. Three numerical examples, including a hierarchical multi-criteria decision-making problem, are used to illustrate how to apply the developed framework, and comparative studies are provided to show its availability and advantages.

FQFD framework for prioritising authenticity and heritage design requirements

Understanding the perceptions of the authenticity attributes of heritage attractions is important for tourism management because heritage attractions have traditionally been divided between those with a primary aim of providing entertainment and others for which conservation and issues of authenticity are pre-eminent. This study establishes a systematic relationship among the concepts of staged authenticity, authenticity attributes, and heritage design requirements based on domestic visitors’ experiences in historical streets. Fuzzy judgement is used to determine the vague cognition of authenticity attributes, and fuzzy quality function deployment and the fuzzy expert system are used to determine the intensity of authenticity attributes to develop heritage design requirements. The results contribute to a better understanding of visitors’ perceptions and valuations of heritage design requirements in the historical streets of Taiwan’s tourist attractions. The study’s findings provide prioritised heritage design requirements, including the requirements of a unique experience, substantial feeling, a pleasant experience, and spiritual characteristics, which can be used to determine interesting directions for heritage design.

Evaluation and Prediction of Water Resources Based on AHP

Nowadays, the shortage of water resources is a threat to us. In order to solve the problem of water resources restricted by varieties of factors, this paper establishes a water resources evaluation index model (WREI), which adopts the fuzzy comprehensive evaluation (FCE) based on analytic hierarchy process (AHP) algorithm.After considering influencing factors of water resources, we ignore secondary factors and then hierarchical approach the main factors according to the class, set up a three-layer structure. The top floor is for WREI. Using analytic hierarchy process (AHP) to determine weight first, and then use fuzzy judgment to judge target, so the comprehensive use of the two algorithms reduce the subjective influence of AHP and overcome the disadvantages of multi-level evaluation. To prove the model, we choose India as a target region. On the basis of water resources evaluation index model, we use Matlab and combine grey prediction with linear prediction to discuss the ability to provide clean water in India and the trend of India’s water resources changing in the next 15 years. The model with theoretical support and practical significance will be of great help to provide reliable data support and reference for us to get plans to improve water quality.

A Novel Reliability Evaluation Method Based on RBD and AHP for Industrial Network Systems

Since each component has different impacts on reliability of the industrial network system, a multi-layer reliability evaluation method was proposed in this paper. Firstly, in order to construct multi-layer reliability evaluation system, a framework of industrial network system was introduced based on analytic hierarchy process (AHP). Secondly, a multi-layer reliability evaluation model with weight coefficient of components was proposed based on reliability block diagram (RBD). Thirdly, the simple rule-based fuzzy judgment and risk priority number (RPN) were applied to determining weight coefficient. Last, a reliability evaluation case of the industrial network system for an electronic automatic assembly line was studied. It shows that the proposed method is more reasonable than the conventional reliability analysis method, and the reliability prediction result is consistent with the engineering practice.

Fuzzy Hybrid MCDM Model for Ranking the Agricultural Water Demand Management Strategies in Arid Areas

In this paper, a fuzzy Multi Criteria Decision Making (MCDM) model is proposed for considering the uncertainty of expert’s opinion in decision making of agricultural water demand management. The performance of Analytical Hierarchy Process (AHP) model was evaluated, and the hybrid model of Modified Technique for Order of Preference by Similarity to Ideal Solution (MTOPSIS) and AHP are introduced in non-fuzzy, MTOPSIS-AHP (MTAHP), and Fuzzy MTOPSIS-AHP (FMTAHP) setting, and the result of them were compared. Sensitivity analyses of tested fuzzy MCDM model was carried out in 3 separate steps of aggregation of individual fuzzy judgments, fuzzy distances values for fuzzification and ranking of fuzzy numbers. In this research, Coefficient of Variation (CV) index of final rates was proposed to evaluate the performance of MCDM models. The results of this paper showed that the geometric mean method is better for aggregation of individual fuzzy judgments. The results showed that non-fuzzy proposed model, MTAHP provided better ranking resolution among tested non-fuzzy MCDM models and only the proposed FMTAHP model significantly increased the CV index of final rates and improve the results resolution. Finally, the proposed MTAHP and FMTAHP models introduced as the best models for ranking alternatives by high resolution in non-fuzzy and fuzzy environment, respectively.

Genetic algorithm based hybrid approach to solve fuzzy multi-objective assignment problem using exponential membership function.

This paper presents a genetic algorithm based hybrid approach for solving a fuzzy multi-objective assignment problem (FMOAP) by using an exponential membership function in which the coefficient of the objective function is described by a triangular possibility distribution. Moreover, in this study, fuzzy judgment was classified using α-level sets for the decision maker (DM) to simultaneously optimize the optimistic, most likely, and pessimistic scenarios of fuzzy objective functions. To demonstrate the effectiveness of the proposed approach, a numerical example is provided with a data set from a realistic situation. This paper concludes that the developed hybrid approach can manage FMOAP efficiently and effectively with an effective output to enable the DM to take a decision.

Research on C2C- to-B2C Transformation Based on the Fuzzy Comprehensive Evaluation Method

C2C-to-B2C transformation, as the inevitable development trend of the Chinese ecommerce, involves many uncertain indexes. The Paper adopts the quantitative and qualitative method to build the index system of the C2C-to-B2C transformation, confirms indexes playing the role in the transformation, and sorts out evaluation factor set and judgement set. And the Paper ensure the weight of evaluation factors by the analytic hierarchy process, confirms the membership degree of indexes to the judgement set baseed on the questionnaire survey, build the single-factor fuzzy judgement to do the comprehensive fuzzy judgement and analysis for each index, and then supply a constructive and instructive way for the transformation-seeking and in-transformation ecommerce.

A Group Decision Framework with Intuitionistic Preference Relations and Its Application to Low Carbon Supplier Selection.

This article develops a group decision framework with intuitionistic preference relations. An approach is first devised to rectify an inconsistent intuitionistic preference relation to derive an additive consistent one. A new aggregation operator, the so-called induced intuitionistic ordered weighted averaging (IIOWA) operator, is proposed to aggregate individual intuitionistic fuzzy judgments. By using the mean absolute deviation between the original and rectified intuitionistic preference relations as an order inducing variable, the rectified consistent intuitionistic preference relations are aggregated into a collective preference relation. This treatment is presumably able to assign different weights to different decision-makers’ judgments based on the quality of their inputs (in terms of consistency of their original judgments). A solution procedure is then developed for tackling group decision problems with intuitionistic preference relations. A low carbon supplier selection case study is developed to illustrate how to apply the proposed decision model in practice.

A new fuzzy decision-making approach for selecting new product development project

The most crucial factor that survives enterprises under stiff competition is the success of new product development project; thus, the new product development project selection has become the vital concerns of R&D managers. The initial stage of the project is filled with uncertainties and complexities, which significantly deteriorate the success of product development and product launch. Previous researches focus on helping enterprises determine a set of good product ideas; however, when proceeding to the product development stage after the fuzzy front end, a best product idea should be selected to form a new product development project to create anticipated profits and develop competitive advantage. Therefore, this study proposes a potential project selection model, which combines optimal aggregation method and effective fuzzy weighted average to assist decision maker to achieve the best consistency of fuzzy judgments, and generates a single synergistic index project fuzzy synthetic rating that considers both risk and performance. The project fuzzy synthetic rating index is then used to help make the project Go-Kill decision, and the remaining survival projects are next prioritized to filter the best project. This model can efficiently assist R&D managers in dealing with both uncertainties and complexities when making new product development project screening decision and can reduce decision bias and produce new product development project with the highest possibility of generating expected profit.

Optimization Analysis of Seismic Damage Evaluation Model Based on Fuzzy Analytical Hierarchy Process

The establishment of fuzzy judgement matrix plays an important role in the accuracy of seismic damage assessment using Fuzzy Analytic Hierarchy Process (FAHP). The optimization analysis is mainly focus on the fuzzy judgement matrix because the important value of each two influencing factors is given by the seismic damage experience and seismic design theory subjectively. In this paper, the initial fuzzy judgement matrix has been set up and the assessment results are given by them. Optimization analysis of single factor is carried out in the adjustment of fuzzy judgement matrix to obtain the best assessment results under the assumption of keeping the fuzzy evaluation matrix of index layer unchangeable. The result shows that accuracy of assessment calculated by the optimal fuzzy judgement matrix has been improved by 1.48%.

Consistency analysis and group decision making based on triangular fuzzy additive reciprocal preference relations

Triangular fuzzy numbers are effective in modeling imprecise and uncertain information, and have been widely applied in decision making. This paper uses a cross-ratio-expressed triplet to characterize a positive triangular fuzzy number, and introduces notions of cross-ratio-expressed triangular fuzzy numbers (CRETFNs) and triangular fuzzy additive reciprocal preference relations (TFARPRs). We present transformation methods between TFARPRs and triangular fuzzy multiplicative reciprocal preference relations, and develop operational laws of CRETFNs, such as complement, addition, multiplication and power. A cross-ratio-expressed triangular fuzzy multiplication based transitivity equation is established to define multiplicative consistency of TFARPRs. The new consistency captures Tanino's multiplicative consistency among the cross-ratio-expressed modal values, and geometric consistency of the interval fuzzy preference relation constructed from lower and upper support values of cross-ratio-expressed triangular fuzzy judgments. Some desirable properties are furnished for multiplicatively consistent TFARPRs. We propose a cross-ratio-expressed triangular fuzzy weighted geometric operator to aggregate CRETFNs, and extend it to fuse TFARPRs. Score and uncertainty index functions are defined and employed to devise a novel comparison method for CRETFNs. A detailed procedure is put forward to solve group decision making problems with TFARPRs. Six numerical examples are provided to illustrate the validity and applicability of the proposed models.

Condition Assessment Model for Subsection Vacuum Switch in Service Based on Fuzzy Synthetic Evaluation

In order to solve the problems of subsection vacuum switch repair deficiency and blind repair and to improve the accuracy of the subsection vacuum switch condition assessment we put forward a strategy based on the theory of fuzzy evaluation. Firstly, a layered evaluation index system on the base of preventive experiments, including working surroundings, operation history, maintenance records, and accessories section and so on is built. Then, the relative impairment degree is introduced to describe the relative grade of subsection vacuum switch changing from actual conditions to faults. The member functions for qualitative indices and the quantitative indices are respectively determined with helps of a fuzzy statistic method and a fuzzy distribution method. An operation condition evaluation model evaluates the state of every grade and gives a comprehensive assessment of subsection vacuum switch, is established on the base of the fuzzy synthetic judgment. Example analysis shows t the method for the safe operation of the transformer condition assessment of reliability is higher and more accurate.

A new approach for deriving fuzzy global priorities in fuzzy analytic network process

This paper proposes a new approach for deriving fuzzy global priorities in fuzzy analytic network process. Due to the convergence problem in taking the limit of the fuzzy supermatrix, it is relatively difficult to generate fuzzy global priorities from fuzzy analytic network process. The presented m ethodology solves the convergence problem by producing a normalized fuzzy supermatrix and raising it to the limiting power based on a linear goal programming model. Consequently, the fuzzy global priorities can be extracted from the fuzzy limiting supermatrix, whose fuzzy column vectors are normalized and identical. The approach is applicable for triangular, interval and trapezoidal fuzzy cases. Finally, two examples are given. One illustrates the effectiveness of the proposed approach and the other demonstrates the use of the obtained fuzzy global priorities in reflecting the uncertainty of the order caused by fuzzy judgments of the expert.

110 kV通用设计变电站能效评估模型研究

经济的飞速发展离不开电力，而大量变电站的投运所带来的能源消耗问题越来越受到重视，评估变电站的运行管理的能效，从而提高变电站能效水平，对于实现绿色环保变电站的建设意义重大。本文通过对内蒙古东部地区现有的110 kV通用设计变电站的实地调查和测量统计，研究变电站的运行管理方法和电力设备的用能特点，采集反应变电站能耗的相关数据，提出能效评估的指标体系，结合国家行业标准，确定基于层次分析法的各因子在变电站能效中的权重，最后利用模糊评判法对110 kV通用设计变电站能效进行综合评定，从而得到完整的能效评估体系。利用实际测量的变电站能效数据对模型进行验证，证明了其可行性，为110 kV通用设计变电站的能效优化提供了指导。 The rapid development of economy is inseparable from the power, and the energy consumption brought by the operation of a large number of substations attracts more and more attention. It is of great significance to evaluate the energy efficiency of substation operation and management so as to improve the energy efficiency of substations. Based on the investigation and measurement of 110 kV universal design substation in the east of Inner Mongolia, this paper studies the operation and management methods of substation and the energy consumption characteristics of the power equipment, collects the data which reflects energy consumption of the substation and puts forward the energy efficiency evaluation index system. Finally, the energy efficiency of 110 kV universal design substation is evaluated synthetically by fuzzy judgment method, and then a complete energy efficiency evaluation system is obtained by combining the national industry standard and the weight of each factor based on AHP in the energy efficiency of the substation. The feasibility of the model is proved by the actual measured energy efficiency data of the substation, which provides the guidance for the energy efficiency optimization of the 110 kV universal design substation.

A New System of Face Recognition: Using Fuzziness and Sparsity

In this article, a new human face recognition scheme is proposed. The proposed system is based on the sparsity and fuzziness, and utilizes independent component analysis (ICA). The scheme includes four parts: a fuzzy comprehensive judgment model for estimating whether the information carried by training samples is enough or not, a proper edge extraction operator to discover more hidden information for single image, ICA feature extractor, and a sparse representation model for correlation coefficient calculation to classify testing samples. In view of the intrinsic patterns of gray information distribution of face images, a weighted fuzzy distance for judgement model and cluster analysis is proposed. The new proposed method is tested on ORL, FERET and UMIST databases. The experiment results demonstrate and illustrate the feasibility of the proposed method and the effective performances on recognition rate.

Multi-hierarchical fuzzy judgment and nested dominance relation of rough set theory-based environmental risk evaluation for tailings reservoirs

Environmental risk assessment of tailings reservoir assessment system is complex and has many index factors. In order to accurately judge surrounding environmental risks of tailings reservoirs and determinate the corresponding prevention and control work, multi-hierarchical fuzzy judgment and nested dominance relation of rough set theory are implemented to evaluate them and find out the rules of this evaluation system with 14 representative cases. The methods of multi-hierarchical fuzzy evaluation can overall consider each influence factor of risk assessment system and their mutual impact, and the index weight based on the analytic hierarchy process is relatively reasonable. Rough set theory based on dominance relation reduces each index attribute from the top down, largely simplifies the complexity of the original evaluation system, and considers the preferential information in each index. Furthermore, grey correlation theory is applied to analysis of importance of each reducted condition attribute. The results demonstrate the feasibility of the proposed safety evaluation system and the application potential.