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[in Japanese]
Article type: Article
1996 Volume 8 Issue 6 Pages
983-
Published: December 15, 1996
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Haruki IMAOKA
Article type: Article
1996 Volume 8 Issue 6 Pages
984-
Published: December 15, 1996
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Tsutomu SAINEN
Article type: Article
1996 Volume 8 Issue 6 Pages
985-992
Published: December 15, 1996
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Shigeru KOMAI
Article type: Article
1996 Volume 8 Issue 6 Pages
993-998
Published: December 15, 1996
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Masayuki OSUMI
Article type: Article
1996 Volume 8 Issue 6 Pages
999-1006
Published: December 15, 1996
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Fumiko NAWATA
Article type: Article
1996 Volume 8 Issue 6 Pages
1007-1015
Published: December 15, 1996
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Takao FURUKAWA, Jin Wang, Akio YUDA, Masayoshi KAMIJO, Yoshio SHIMIZU
Article type: Article
1996 Volume 8 Issue 6 Pages
1016-1022
Published: December 15, 1996
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Haruki IMAOKA
Article type: Article
1996 Volume 8 Issue 6 Pages
1023-1027
Published: December 15, 1996
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Toshihide IBARAKI
Article type: Article
1996 Volume 8 Issue 6 Pages
1028-1031
Published: December 15, 1996
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Article type: Bibliography
1996 Volume 8 Issue 6 Pages
1032-1035
Published: December 15, 1996
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Kouji MIURA, Jun OZAWA, Takeshi IMANAKA, Masaaki TSUNEKAWA
Article type: Article
1996 Volume 8 Issue 6 Pages
1036-1038
Published: December 15, 1996
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Hisao ISHIBUCHI
Article type: Article
1996 Volume 8 Issue 6 Pages
1039-1041
Published: December 15, 1996
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Andreas Bastian
Article type: Article
1996 Volume 8 Issue 6 Pages
1042-1043
Published: December 15, 1996
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Tomomi HASHIMOTO
Article type: Article
1996 Volume 8 Issue 6 Pages
1044-1045
Published: December 15, 1996
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Yasuji KANAI
Article type: Article
1996 Volume 8 Issue 6 Pages
1046-1048
Published: December 15, 1996
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Hugang HAN
Article type: Article
1996 Volume 8 Issue 6 Pages
1049-1051
Published: December 15, 1996
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[in Japanese]
Article type: Article
1996 Volume 8 Issue 6 Pages
1055-
Published: December 15, 1996
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[in Japanese]
Article type: Article
1996 Volume 8 Issue 6 Pages
1055-1056
Published: December 15, 1996
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[in Japanese]
Article type: Article
1996 Volume 8 Issue 6 Pages
1057-
Published: December 15, 1996
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[in Japanese]
Article type: Article
1996 Volume 8 Issue 6 Pages
1057-
Published: December 15, 1996
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Andreas BASTIAN, Isao HAYASHI
Article type: Article
1996 Volume 8 Issue 6 Pages
1058-1065
Published: December 15, 1996
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Although genetic algorithms (GAs) are more and more employed as optimization tools of fuzzy logic based systems, the user is faced with the problem of selecting the right parameters of the GAs, such as the population size, the generation gap, the crossover and the mutation rate and so on. Unfortunately, the selection of those parameters require experience and knowledge. Moreover, it is evident, that those parameters are to change dynamically in accordance to the optimization stage. For example, in the beginning a large population is needed, while later near to convergence, most of the population member will be similiar, thus only wasting computing time. The idea proposed in this work is therefore a knowledge-based approachfordynamically adaptation of the GAs. The knowledge is expressed in form of fuzzy logic IF-THEN rules. It will be shown, that such a knowledge-based GAs is superior to a static GAs. Also, in the final stage of the optimization, we optimize the defuzzification.
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Norihiko MASUDA, Kazuo SHIGEMATSU
Article type: Article
1996 Volume 8 Issue 6 Pages
1066-1072
Published: December 15, 1996
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In order to assess the uncertainty, verbal probability judgement is a more natural and easier device than the direct numerical assessment. We propose a new procedure to measure subjective probability by means of verbal probability judgment. This procedure provides the assessment of subjective probability in terms of the distribution rather than the unique value of estimate.There are two aspects of uncertainty involved in this judgment. The one is the uncertainty of subjects' belief, which means it cannot be represented by a unique value and instead we assume subjects' belief is distributed as a truncated normal distribution. The other is the unvertainty associated with each of verbal expressions. This uncertainty is represented as trapezoidal membership functions. Based on these two assumptions, we obtain the likelihood of probability (belief) value when subjects rate the appropriateness of each of verbal expressions for a particular event. Assuming that the prior distributions for parameters are uniform, we finally obtain the subjective probability distribution for each of eight events which we assigned.We measured subjective probabilities about various unvertain events. They agreed with our intuitions and they were more consistent than direct numerical assessments when available.
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Xiao-Zong YANG, Kazuhiko SUZUKI, Yukiyasu SHIMADA, Hayatoshi SAYAMA
Article type: Article
1996 Volume 8 Issue 6 Pages
1073-1086
Published: December 15, 1996
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It is required to deal with the unvertainty information about process abnormal knowledge and running data, the heuristic experience of specialist, and the fuzziness of language for knowledge representation for developing an actual process fault diagnostic system. This paper presents an approach to construction of a process fault diagnostic system by use of fault tree analysis and fuzzy reasoning. The production rules are constructed on the basis of the information about minimal cut sets of a fault tree and the fault propagation in the process. The fuzziness about the consequent part in a rule is determined by proposing fuzzy failure analysis, and stored in the knowledge base as the form of failure possibility distribution. We apply fuzzy reasoning to fault diagnosis by matching the pattern of the grades of process operation data with the knowledge base. The positive causes and their diagnostic grades of process abnormality are estimated from the results of fuzzy reasoning. Finally, we show and verify the practivality of the proposed method by applying the diagnostic system to a laboratory plant.
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Gaku ADACHI, Takeshi FURUHASHI, Yoshiki UCHIKAWA
Article type: Article
1996 Volume 8 Issue 6 Pages
1087-1095
Published: December 15, 1996
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Recently fuzzy logic has been utilized for non-linear controls, and many research studies on design methods have also been reported. The design method based on fuzzy models of controlled objects is effective in reducing the amount of labor in control knowledge acquisition, and also enables to design to design controllers for controlled objects without control experts. However, no study on design method of fuzzy controllers, which utilizes the feature of fuzzy controls in that control rules are easy to understand, and considers required responses of control systems, has been reproted.This paper presents an automatic design method of fuzzy controllers using the "Rule-to-Rule Mapping" method for describing the dynamical behavior of fuzzy control systems. The fuzzy controller is designed based on both linguistic specifications translated from required responses of the control system and the fuzzy model of the controlled object. The feasibility of the method is examined by experiments with an inverted pendulum. The results show that the method is effective to satisfy the linguistic requirements.
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Tomonobu SENJYU, Shingo ASHIMINE, Katsumi UEZATO
Article type: Article
1996 Volume 8 Issue 6 Pages
1096-1103
Published: December 15, 1996
Released on J-STAGE: January 08, 2018
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The position control ability of DC servomotors is affected by parameter variations and disturbance torque. A mathematical plant model is usually used for controlling DC servomotors, however, accurate parameter measurement is very difficult and parameters vary with operating conditions, for example, temperature rise or saturation effects.In recent years, the DC servocontroller using the equivalent disturbance torque observer which compensates parameter variations and disturbance torque has been proposed, high-performance control of the servomotor has been achieved. However, the estimated disturbance torque by the equivalent disturvance torque observer has estimation error, therefore, the control method taking account of estimation error is necessary.In this paper, the robust position control method of DC servomotor with the equivalent disturbance torque observer and the feedback controller is proposed. The estimation error for disturbance torque is identified by fuzzy reasoning. The influence of estimation error is restrained by the adaptive feedback gain law using the identified estimation error.The useful features and validity of the proposed control method are confirmed by computer simulations and experiments.
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Hiroyuki INOUE, Katsuari KAMEI, Kazuo INOUE
Article type: Article
1996 Volume 8 Issue 6 Pages
1104-1115
Published: December 15, 1996
Released on J-STAGE: January 08, 2018
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Fuzzy reasoning has developed as a method that can express our knowledge and has been applied to various fields, for example fuzzy control. In fuzzy reasoning, expert knowledge is expressed by fuzzy if-then rules. But, there is the problem that it is very difficult to tune its membership functions and reasoning rules. In addition, it is difficult to obtain expert knowledge in large-scale systems with many inputs and outputs. Therefore, many techniques have been suggested to automatically tune or generate membership functions and fuzzy if-then rules.In this paper, we present an automatic generation technique for fuzzy if-then rules by genetics-based machine learning. We consider flexible shape and location of fuzzy rules to obtain fuzzy rules of nearly human sense. In this method, the antecedent part and the consequent part of each rule are expressed by a hyper-cone membership function. The genetic algorithm decides the location and the radius of each hyper-cone membership function in the input and output spaces. We add genetic information whether each rule is fired or not, and delete needless rules using this information and a method of forgetting. We applied this method to the car pursuit control problem and the trailer-track back-up control problem.
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Takeshi ITOH, Hiroaki ISHII
Article type: Article
1996 Volume 8 Issue 6 Pages
1116-1124
Published: December 15, 1996
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For shortest path problems, the distances associated with networks are assumed to be constant. But, in the real world, such case is rare. This paper formulates the problem in which such distances are L-R fuzzy numbers. The aim is to find the path which the corresponding possibility that its distance is larger than a certain threshold is maximum. That is, we introduce a fuzzy goal, and attempt to maximize the possibility measure, which is a kind of fuzzy measure. Further, we propose an efficient algorithm solving the problem by extending {bf Dijkstra}'s algorithm.
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Masahiro INUIGUCHI, Masatoshi SAKAWA
Article type: Article
1996 Volume 8 Issue 6 Pages
1125-1133
Published: December 15, 1996
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In this paper, we discuss a soft optimal solution which is robust against the fluctuations of the objective coefficient values in the setting of the linear programming problem. A soft optimal solution stands for a feasible solution whose objective function value is near the optimal value of the linear programming problem. The ambiguity of the objective coeffcient values is represented by possibility distributions. In order to express the nearness of the objective function value, we introduce a fuzzy goal defined on the deviation from the optimal value. A necessity measure is adopted for representing the robustness and a necessarily fuzzy optimal solution set is defined. The solution having the highest membership value of the necessarily fuzzy optimal solution set can be considered as the most reasonable solution and called the best necessarily fuzzy optimal solution. A method of the best necessarily fuzzy optimal solution is proposed.
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Kohei NOMOTO, Wakasa KISE, Yoshio KOSUGE
Article type: Article
1996 Volume 8 Issue 6 Pages
1134-1143
Published: December 15, 1996
Released on J-STAGE: January 08, 2018
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When we wish to make a decision on the best approach to carry out a certain task at the present time, we usually refer to past cases whose conditions are similar to those of the present case. It is consequently useful to provide a decision maker with a system which retrieves the past cases. Since the completely same conditions of past cases to those of the present case do not exist, the system should evaluate a grade of the similarity and should output the retrieved cases accompanied with the grade. In the similar case retrieval, the cases are labeled with a number of indexes and they characterize the cases. The each index has a set of index attribute values and only one of them is designated to the corresponding index. A fuzzy thesaurus which shows quantitative relations of the index attribute values is, then, useful for the similar case retrieval. There is a conventional algorithm to generate a fuzzy thesaurus for document retrieval, so far, which is based on cooccurrences of a pair of keywords in the whole of the contents.It is, however, practical to generate the fuzzy thesaurus using only electronic data of the index. A problem of this case is that the cooccurrences in an index is not observed because there is only one index attribute value in each index.In this paper, a new algorithm to generate a fuzzy thesaurus using only the electronic data of index is presented and its application to the similar case retrieval is shown. This algorithm makes use of two indexes in a case and observes cross-occurrences of a pair of index attribute values in the two indexes. Using an operation, which we call sum-min composition, indirect relation of a pair of index attribute values in an index is evaluated based on the cross-occurrences and the fuzzy thesauri are generated.A decision support system to plan a rescue operation against a disaster has been developed. This system uses fuzzy thesauri to retrieve past rescue operations which are similar to the present condition. The presented algorithm has been applied to generate these fuzzy thesauri.
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Toshihiro SHIBANO, Masatoshi SAKAWA, Hidenobu OBATA
Article type: Article
1996 Volume 8 Issue 6 Pages
1144-1153
Published: December 15, 1996
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In this paper, by considering the experts' imprecise or fuzzy understanding of the nature of the parameters in the problem-formulation process, multiobjective 0-1 programming problems involving fuzzy numbers are formulated. Using the α-level sets of the fuzzy numbers, the corresponding nonfuzzy α-programming problem is introduced.Through the introduction of an extended Pareto optimality concept, if the decision maker specifies the degree α and the reference objective values, corresponding extended Pareto optimal solution can be obtained by solving the augmented minimax problem through genetic algorithms with double strings. Then an interactive decision making method for deriving a satisficing solution for the decision maker efficiently from an extended Pareto optimal solution set is presented. An illustrative numerical example is provided to demonstrate the feasibility and efficiency of the proposed method.
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Masayuki MURAKAMI, Nakaji HONDA
Article type: Article
1996 Volume 8 Issue 6 Pages
1154-1159
Published: December 15, 1996
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Auto exposure (AE) is an important function of video cameras to adjust the image luminance. In this paper, the exposure control systems of the AE using color information are discussed. Current AE systems detect the backlighting and excessive frontlighting, and conduct the exposure control putting emphasis on the main object by compensating the exposure. This backlighting / excessive frontlighting compensation is characterized by adjusting the luminance of the main object where it is appropriate, causing the background to become worse. However, in the AE systems which have been proposed so far, the compensation amount is determined according to the degree of backlighting and excessive frontlighting, regardless of the importance of the background. Since these AE systems control the exposure obtaining information from the luminance signal, judging the importance of the background with only luminance information is difficult. The proposed exposure control system employs "hue" and "chroma" of pixels to derive the importance of the background, and determines a compensation amount by fuzzy reasoning.Simulations of AE are carried out for the conventional system and proposed one. The performance of each system is tested through the assessment experiments of human subjects for image samples of simulation results, and the proposed system is shown to be efficient for AE.
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1996 Volume 8 Issue 6 Pages
1160-1164
Published: December 15, 1996
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Article type: Index
1996 Volume 8 Issue 6 Pages
T1-T8
Published: December 15, 1996
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