• 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.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.787-790
• /
• 1997

This paper proposes a method which selects essential elements in a human evaluation model using the Choquet integral based on fuzzy measures, and applies the model to the evaluation of human interface. Three kinds of concepts are defined to select essential elements. Increment Degree implies the increment degree from fuzzy measures of composed elements to the fuzzy measure of a combined element. Average of Increment Degree of an element means the relative possibility of superadditivity of the fuzzy measure of each combined element. Necessity Degree means the selection degree of each combined element as a result of the human evaluation. A task experiment, which consists of a static work and two dynamic works, is performed by the use of some human interfaces. In the experiment, (1) a warning sound which gives an attention to subjects, (2) a color vision which can be distinguished easily or not, (3) the size of working area and (4) a response of confirmation that is given from an interface, are considered as human interface elements. Subjects answer the questionnaire after the experiment. From the data of the questionnaire, fuzzy measures are identified and are applied to the proposed model. Effectiveness of the proposed model is confirmed by the comparison of human interface elements extracted from the proposed model and those from the questionnaire.

• 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.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.20 no.2
• /
• pp.267-272
• /
• 2010

This paper suggests an evaluation method through corporate culture's evaluation model considering the relationship and affection between types and elements of corporate culture. 314 data obtained from the members of small and medium enterprises analyzed the relationship by the correlation analysis, and the degree affecting rate the corporate culture types by the regression analysis. Finally, fuzzy system was used to analyze the evaluation model of the corporate culture type. The evaluation model of the corporate culture types in this paper is mixed possibility and necessity sides and showed the usefulness through reviewing the model which has an identification problem of the fuzzy system estimated fuzzy relation matrix for corporate culture types using the model.

• Journal of the Korean Society of Fisheries and Ocean Technology
• /
• v.59 no.1
• /
• pp.44-54
• /
• 2023

In this study, the second-order Nomoto's nonlinear expansion model was implemented as a Tagaki-Sugeno fuzzy model based on the heading angular velocity to design the automatic steering system of a ship considering nonlinear elements. A Tagaki-Sugeno fuzzy PID controller was designed using the applied fuzzy membership functions from the Tagaki-Sugeno fuzzy model. The linear models and fuzzy membership functions of each operating point of a given nonlinear expansion model were simultaneously tuned using a genetic algorithm. It was confirmed that the implemented Tagaki-Sugeno fuzzy model could accurately describe the given nonlinear expansion model through the Zig-Zag experiment. The optimal parameters of the sub-PID controller for each operating point of the Tagaki-Sugeno fuzzy model were searched using a genetic algorithm. The evaluation function for searching the optimal parameters considered the route extension due to course deviation and the resistance component of the ship by steering. By adding a penalty function to the evaluation function, the performance of the automatic steering system of the ship could be evaluated to track the set course without overshooting when changing the course. It was confirmed that the sub-PID controller for each operating point followed the set course to minimize the evaluation function without overshoot when changing the course. The outputs of the tuned sub-PID controllers were combined in a weighted average method using the membership functions of the Tagaki-Sugeno fuzzy model. The proposed Tagaki-Sugeno fuzzy PID controller was applied to the second-order Nomoto's nonlinear expansion model. As a result of examining the transient response characteristics for the set course change, it was confirmed that the set course tracking was satisfactorily performed.

• 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.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.4 no.1
• /
• pp.90-96
• /
• 2004

A generalized net model of a training process with modified fuzzy marks in answers of the trained objects and their current and total modified fuzzy evaluation, tharning themes, estimation criteria and others are discussed and interpreted.

• Korean Journal of Construction Engineering and Management
• /
• v.1 no.1 s.1
• /
• pp.53-62
• /
• 2000

This study proposes FREES(Fuzzy Risk Evaluation Expert System) for analyzing and evaluating risks occurring during the construction process. The feasibility of this system model was tested by virtual scenario. For the development of the model, at first, risk breakdown structure was established based on risks identified in the existing researches, that is quantitative and qualitative. FREES can reflect human cognition process in the risk analysis and evaluation by adopting artificial intelligence fuzzy theory, differentiating the existing quantitative analysis model. The FREES can be applied to all the project phases from planning to operation & maintenance stage.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.06a
• /
• pp.517-521
• /
• 1998

DEA(data envelopment analysis) is a non-parametric technique for measuring and evaluating the relative efficiencies of a set of entities with common crisp inputs and outputs. In fact, in a real evaluation problem input and output data of entities often flucturate. These fluctuating data can be represented as linguistic variables characterized by fuzzy numbers. Based on a fundamental CCR model, a fuzzy DEA model is proposed to deal with fuzzy input and output data, Furthermore, a model that extends a fuzzy DEA to a more general case is also proposed with considering the relation between DEA and RA (regression analysis) . the crisp efficiency in CCR modelis extended to an L-R fuzzy number in fuzzy DEA problems to reflect some uncertainty in real evaluation problems.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.10a
• /
• pp.31-36
• /
• 1998

This paper proposes a method to select essential elements in a human evaluation model using the Choquet integral based on fuzzy measures and applies the model to the evaluation of human interface. Three kinds of concepts, Increment Degree, average of Increment Degree, Necessity coefficient, are defined. The proposed method selects essential elements by the use of the Relative necessity coefficient. The proposed method is applied to the analysis of human interface. In the experiment, (1) a warning sound, (2)a color vision, (3) the size of working area, (4) a response of confirmation, are considered as human interface elements. subjects answer the questionnarie after the experiment. From the data of questionnaire, fuzzy measures are identified and are applied to the proposed model. effectiveness of the proposed model is confirmed by the comparison of human interface elements extracted from the proposed model and those from the questionnarie.