• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2000.11a
• /
• pp.25.2-31
• /
• 2000

Recently, Fuzzy theory has been applied in evaluation problem. Fuzzy evaluation based on Fuzzy theory can accommodate fuzziness of judgement with people through introducing Fuzzy measure. Representative Fuzzy evaluation is Fuzzy Integral using Fuzzy measure. Definite methodology using Fuzzy Integral HFI(Hierarchical Fuzzy Integrals), HFEA(Hierarchical Fuzzy Evaluation Algorithm), HFP(Hierarchical Fuzzy Process), etc. In this paper, we deal with problem identifying evaluation value using Fuzzy Relation Equation at these Fuzzy evaluation. We verify relation between Input data and Output data through @-operation and apply this to HFP. And that we verify evaluation value which objects of evaluation are able to possess.

• Journal of the Korean Society for Railway
• /
• v.9 no.4 s.35
• /
• pp.432-440
• /
• 2006

Prior to the service evaluation, many kinds of its attributes must be identified on the basis of rational decision owing to complexity and ambiguity inherent in logistics service. there are so many evaluation methods but they are not applicable to logistics service the have property of non-additivity and overlapped attributes. Therefore, probability measure can not used to evaluate logistics service but Fuzzy Measure is required. And the method should be easy to calculate it Recently Fuzzy theory has been applied in Various evaluation problem. Fuzzy evaluation based on Fuzzy theory can accommodate fuzziness in judgement with people through introducing Fuzzy Measure. In this paper, Hierarchical Fuzzy Process is applied to evaluate level of logistics service in Korail and the biggest six logistics companies in the korea which is called 3PL Company. Also Fuzzy Relation Equation which is problem identifying evaluation value at these fuzzy evaluation is applied to verify relation between Input and Output data through @-operation. Therefore, we apply this Fuzzy Relation Equation to Hierarchical Fuzzy Process and verify evaluation value which objects of evaluation are able to possess.

• Journal of Korean Port Research
• /
• v.13 no.1
• /
• pp.79-86
• /
• 1999

This paper deals with the evaluation problem of complex systems by introducing a fuzzy approach. The authors are functionally supposing a hierarchical structure model of a complex system and give light on the following problems. First for the purpose of clarifying the characteristics of measures the property and differences between two method such as linear and fuzzy viewpoint are discussed through two level-down evaluation process. Second the integrated evaluation process which keeps reversibility between hierarchical levels is discussed and obtained some necessary conditions for reversibility of fuzzy evaluation. From these results it is expected that the fuzzy approach overcomes partly the limitation of reductionism at the hierarchical evaluation of complex systems.

• The Journal of Economics, Marketing and Management
• /
• v.10 no.5
• /
• pp.1-6
• /
• 2022

Purpose: To overcome the question that depends too much on expert's subjective judgment in traditional risk identification, this paper structure the multilevel generalized fuzzy comprehensive evaluation mathematics model of the risk identification of project, to research the risk identification of the project. Research design, data and methodology: This paper constructs the multilevel generalized fuzzy comprehensive evaluation mathematics model. Through iterative algorithm of AHP analysis, make sure the important degree of the sub project in risk analysis, then combine expert's subjective judgment with objective quantitative analysis, and distinguish the risk through identification models. Meanwhile, the concrete method of multilevel generalized fuzzy comprehensive evaluation is probed. Using the index weights to analyse project risks is discussed in detail. Results: The improved fuzzy comprehensive evaluation algorithm is proposed in the paper, at first the method of fuzzy sets core is used to optimize the fuzzy relation matrix. It improves the capability of the algorithm. Then, the method of entropy weight is used to establish weight vectors. This makes the computation process fair and open. And thereby, the uncertainty of the evaluation result brought by the subjectivity can be avoided effectively and the evaluation result becomes more objective and more reasonable. Conclusions: In this paper, we use an improved fuzzy comprehensive evaluation method to evaluate a railroad engineering project risk. It can give a more reliable result for a reference of decision making.

• The Journal of Korean Association of Computer Education
• /
• v.6 no.4
• /
• pp.95-113
• /
• 2003

We introduce an AFES(Adaptive Fuzzy Evaluation System) that applies an evaluation system used to existing LCMS(Learning Contents Management System) to a fuzzy reasoning rule. The AFES confers a course level on the learner through a fuzzy diagnostic evaluation before the learner enters a learning course. After the learner completes a learning course through the tailored learning path that is suitable for the learner's level, the AFES confers a final grade on the learner by means of fuzzy final evaluation. The biggest characteristic of the AFES is a grade rule of the final grade. Although different learners get the same number of correct answers to the same number of Questions, AFES flexibly confers the different final grade on the learner by means of the number of 125's fuzzy reasoning rules.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.20 no.2
• /
• pp.362-372
• /
• 1996

Recently, need for the development of the quantification of subjective evaluation is growing for the production of high-touch and high-tech textile products. In this study, Fuzzy theory is utilized for the evaluation of the wear comfort of the various blouses. Result of a new evaluation method and factor scores, validity of the new evalution technique adopted fuzzy theory was crosschecked with the results of fator analysis and factor scores. As results, fuzzy theory was proved to be adequate methodology to objectify the subjective evaluation of the adequacy of clothing which is worn. When DUNCAN'S multiple comparion among median of the fuzzy composite score were compared with the results of factor score, the sensitivity of the test methods tends to increase. Therefore, it is suggested that fuzzy weighted checklist is an alternative evaluation scale for the subjective comparison of the textile products. In addition, individual median of fuzzy composite score value should be treated by statistical for the sensitive analysis of subjective evalution.

• Journal of Korean Port Research
• /
• v.7 no.1
• /
• pp.5-12
• /
• 1993

In complex decision making such as ill-defined system, one of the main problem is how to treat ambiguous aspect of the decision making. According to the complexity and ambiguity of the objective systems, many types of evaluation attributes are necessary for the rational decision and the relationship among the attributes become complex and fuzzy. Fuzzy integral is very effective to evalute the complex system with interaction between attributes but how to save the evaluation efforts in the decision making process of grading the membership of the objects or alternative is the problem to be tackled. Because the more object there are to evaluate, the number of decisions to made increase exponentially. Therefore, this paper aimes to propose a new evaluation algorithm based on fuzzy integral which can save the evaluator's efforts in decision making process. The proposed algorithm is constructed as follows : First, compose the fuzzy measure by introducing AHP(Analytical Hierachy Process) & mutual interaction coefficient. Second, generate fuzzy measure value of monotone family set for calculating the fuzzy integral. The effectiveness of the proposed algorithm is investigated through the example and sensitivity of interaction coefficient is illustrated.

• Journal of Korean Association for Spatial Structures
• /
• v.17 no.2
• /
• pp.53-62
• /
• 2017

This study aims to establish a seismic resistance performance evaluation method that makes sure to secure the seismic resistance performance of the existing mid-low story reinforced concrete structures. This study focuses on the development of the seismic resistance performance evaluation method for the overall seismic resistance performance evaluation on the buildings by applying fuzzy theory. This seismic resistance performance evaluation method considers the mutual relations among the type of force, the type of member, the type of story, and the states of deterioration of the buildings. The total seismic resistance performance index from this method was calculated by the intensity weight of each evaluation item, fuzzy measure, fuzzy integration. Moreover, the evaluation methodology was established in this study to identify the performance level of the Immediate Occupancy, Life Safe, Collapse Prevention by applying the fuzzy theory.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1993.06a
• /
• pp.1226-1229
• /
• 1993

This paper proposes a new on-line fuzzy model identification(ONFID) algorithm in which the fuzzy model evaluation stage is incorporated. The fuzzy model evaluation is performed by the fuzzy equality index which is known to be a useful tool to evaluate the performance of the identified fuzzy model. Then the fuzzy model is updated according to the result of the evaluation. Proposed ONFID algorithm can sensibly identify to the system changes. To show the usefulness of the proposed algorithm, it is applied to the fuzzy model identification problem of the gas furnace and the output prediction problem of the flexible joint manipulator which is a nonlinear system.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.2 no.1
• /
• pp.97-106
• /
• 1996

One of the main problems in evaluating complex objects, such as an ill-defined system, is how to treat ambiguous aspect of the evaluation. Due to the Complexity and ambiguity of the objects, many types of evaluation attributes should be identified based on the rational dsision. One of these attributes is an analytical hierarchy process (AHP). the weight of evaluation attribtes in AHP however comes from the probability measure based on the additivity. Therefore, it is notapplicable to the objects which have the property of non-additivity. In the previous studies by other researchers they intriduced the Hierarchical Fuzzy Integral method or mergd AHP and fuzzy measure for the analysis of the overlaps among the evaluation objects. But, they need more anlyses in terms of transformation of the probability measure into fuzzy measure which fits for the additivity and overlapping coefficient which affects to the fuzzy measure. Considering these matters, this paper deals that, ⅰ) clarifying the relation between the fuzzy and probability measure adopted in AHP, ii) calculating directly the family of fuzzy measure from the overlapping coefficient and probability measure. A simple algorithm for the calculation of fuzzy measures and set family of those from the above results is also proposed. Finally, the effectiveness of the algorithm developed by applying this to the problems for estimation of safety in ship berthing and for evaluation of ports in competition is verified. This implied that the new algoritnm gives better description of the system evaluation.