• Journal of Korean Society of Transportation
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• v.23 no.8 s.86
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• pp.171-179
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• 2005

This paper presents the algorithm using fuzzy inference that preestimates each link speed changed by different kinds of road situations. The elements we are considered are time zone, rainfall probability information and lane control information. This paper is consists of three parts. First of all we set up the fuzzy variables, and preestimate link speed changed by various road situations. For this process, we build the membership functions for each fuzzy variable and establish the fuzzy inference relations to find how fuzzy variables influence on link speed. Second, using backtracking method, we search the shortest route influenced by link speed changed by fuzzy inference. Third, we apply this algorithm to hypothetical network and find the shortest path. As a result, it is shown that this algorithm choose appropriate roundabout path according to the changing road situations.

• Journal of Advanced Marine Engineering and Technology
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• v.19 no.4
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• pp.72-78
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• 1995

The diffusion of fuzzy logic techniques into real applications requires specific software supports which save development time and reduce the programming effort. But we has been lack of a tool devoted to support the design of fuzzy controllers. In this paper, on the basis of the general fuzzy set and .alpha.-cut set decomposition of fuzzy sets, a set of fuzzy reasoning tool(FRT) devoted to support the design of fuzzy dontroller for servo systems is developed. The major features of this tool are: 1) It supports users to analyze fuzzy ingerence status based on input deta and expected results by three-D graphic display. 2) It supports users to prepare input data and expected result. 3) It supports users to tuned scaling factor of membership functions, rules and fuzzy inference. The paper shows how the suggested design tools are suitable to give a consistent answer to the tuning of fuzzy control system. This FRT is expected to exert good performance and devoted to support which the design of fuzzy controller is illustrated in the servo systems.

• Tunnel and Underground Space
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• v.11 no.4
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• pp.289-300
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• 2001

In the design of tunnel, it contains inaccuracy of data, fuzziness of evaluation, observer error and so on. The face observation during tunnel excavation, therefore, plays an important role to raise stability and to reduce supporting cost. This study is carried out to minimize the subjectiveness of observer and to exactly evaluate the natural properties of ground during the face observation. For these purpose, fuzzy set theory and neuro-fuzzy techniques in artificial intelligent techniques are applied to the inference of the RMR value from the observation data. The correlation between original RMR vague and inferred RM $R_{_FU}$ and RM $R_{_NF}$ values from fuzzy set theory and neuro-fuzzy techniques is investigated using 46 data. The results show that good correlation between original RMR value and infected RM $R_{_FU}$ and RM $R_{_NF}$ value is observed when the correlation coefficients are ｜R｜=0.96 and ｜R｜=0.95 respectively. From these results, applicability of fuzzy set theory and neuro-fuzzy techniques to rock mats classification is proved to be sufficiently high enough. enough.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.1
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• pp.31-36
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• 2003

The descriptive grade evaluation system is adopting to solve the problems of pre-exiting system that refers to marks and ranks. However, it increases the work load and creates inconsistencies of the grade evaluations due to teachers subjective evaluations. In this Paper, I suggest a grade evaluation system, applying the Fuzzy reasoning on web for teachers to evaluate students more effectively. Teachers can input the results of the accomplishment assessments. It also evaluates with the Fuzzy reasoning to attain the final evaluation of the subjects. The system also creates descriptive evaluation sentences by abstracting some sentences for evaluation utilizing the properties of the Fuzzy reasoning rules.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.6
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• pp.742-746
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• 2006

Evaluation of learning ability of students is classified a step of diagnostic, formative and summative evaluation. This step-by-step evaluation is the standard of synthesis judgement, from a student's prior learning of preparation state to devotion of learning process and even learning result. In this paper, we propose the method of synthesis learning evaluation which is considered evaluation of each step in using fuzzy inference. In order to get objective evaluation of learning ability, we applied to the weights by evaluation steps. And we reflected defuzzification values of final evaluation membership function interval obtained by fuzzy inference about diagnostic, formative and summative evaluation. As a result, it processes definite inference ensures objectivity and shows validity of the synthesis evaluation method.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.12
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• pp.139-148
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• 1995

In this paper an electro-hydraulic servo system is designed by using a fuzzy control algorithm. In order to drive an optimal fuzzy control system, a simulation program for the control system has been developed. By this program the fuzzifier and defuzzifier, a fuzzy inference method, a fuzzy relational matrix, and a fuzzy inference method are investigated. As a result, Larsen inference method, 9*9 fuzzy relational matrix, and center of area defuzzifier are turned out the best as parameters. Finally this method is compared with the conventional PID algotithm, and showed that the fuzzy control performs better than PID algorithm. The fuzzy control performs very well adap- tation against uncertain disturbances.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.1
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• pp.23-34
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• 1991

This paper is studied for the recognition of occluded objects by fuzzy inference. The images are transformed a group of linear line segments, which is formed local features extracted from curvature points, using polygonal approximation. The features extracted from images are representes to the fuzzified data which is mapped into fuzzy concepts to represent the fuzziness, and the recognition of a model from scenes is performed by fuzzy inference using the production rulse which is generated from the model image. It is considered that the recognition results according to the change of degree of fuzziness in the experiments, and the experimental results for 30 scenes contained 120 models is obtained 92.5% of recognition rate.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.4
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• pp.52-57
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• 2003

A PID parameter tuning method was presented by the fuzzy singleton inference, based on step response-shaping of plant and experience knowledge of expert. The parameter-tuning has tow levels. The higher level determines modified coefficients for the controller based on operator's tuning know-how for characteristics of plant which can not be modeled. The lower level determines specified coefficients based on characteristics of response by Ziegler-Nickel's bounded sensitivity method. The last level parameters tuning of a PID controller is adjusted which the modified and specified coefficients makes adjustment rule, and is adjusted the proper value to each parameters by fuzzy singleton inference. Moreover, proposed the tuning method can reflex exporter knowledge and operator's tuning know-how and fuzzy singleton inference is rapidly operated.

• Journal of Intelligence and Information Systems
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• v.1 no.2
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• pp.17-32
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• 1995

본 논문에서는 추론엔진 (inference engine)내에 퍼지정보 검색부(Fuzzy Information Retrieval part)를 갖는 교통신도 제어 전문가 시스템을 제안한다. 제안하는시스템은 다양하고 복잡한 도로 상화을 고려하여 그에 따른 적절한 주기를 각 도로별로 할당함으로써 원활한 교통 흐름을 제어한다. 추론엔진내의 퍼지정보 검색부는 퍼지 삼각 논리곱을 이용하여 도로의 상황을 분석한 후 각 도로에 맞는 가장 적절한 신호주기를 생성한다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.442-445
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• 2004

본 논문은 유전자 기반 퍼지다항식 뉴럴네트워크(Genetic based fuzzy polynomial neural networks： gFPNN)를 제안한다. gFPNN 구조는 퍼지집합을 기반으로 설계되며, 유전자 알고리즘에 의해 구조 및 파라미터를 최적화한 구조이다. 퍼지집합을 기반으로 설계되어진 퍼지뉴럴네트워크는 간략추론 구조와 선형추론 구조로 설계된다. 본 논문에서는 간략추론 및 선형추론 구조를 통합 및 확장한 퍼지다항식 뉴럴네트워크를 설계한다. 이 구조는 연결가중치를 이용하여 회귀다항식을 네트워크 구조로 표현하며, 간략추론(Type 0), 선형추론(Type 1), 회귀다항식추론(Type 2)을 모두 포함한다. 또한 퍼지규칙 후반부의 다항식 차수를 각 규칙에 대해 다르게 선택할 수 있으며, 일률적인 형식의 구조를 벗어나 주어진 시스템의 특성에 따라 유연한 구조를 설계할 수 있도록 한다. 여기에 더하여, 네트워크 구조와 파라미터 동조에 유전자 알고리즘을 적용하며, 구조와 파라미터 동정에 대한 효율적인 방법을 논의한다. 제안된 모델의 평가를 위해 수치예제를 이용한다.