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[in Japanese]
Article type: Article
2000 Volume 12 Issue 4 Pages
459-
Published: August 15, 2000
Released on J-STAGE: January 07, 2018
JOURNAL
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Makoto FUJIYOSHI
Article type: Article
2000 Volume 12 Issue 4 Pages
460-
Published: August 15, 2000
Released on J-STAGE: January 07, 2018
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Makoto IIDA
Article type: Article
2000 Volume 12 Issue 4 Pages
461-464
Published: August 15, 2000
Released on J-STAGE: January 07, 2018
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Kaori YOSHIDA
Article type: Article
2000 Volume 12 Issue 4 Pages
465-468
Published: August 15, 2000
Released on J-STAGE: January 07, 2018
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Shoji YAMADA
Article type: Article
2000 Volume 12 Issue 4 Pages
469-476
Published: August 15, 2000
Released on J-STAGE: January 07, 2018
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Seiji INOKUCHI
Article type: Article
2000 Volume 12 Issue 4 Pages
477-486
Published: August 15, 2000
Released on J-STAGE: January 07, 2018
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Takashi NAKAJIMA
Article type: Article
2000 Volume 12 Issue 4 Pages
487-492
Published: August 15, 2000
Released on J-STAGE: January 07, 2018
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Eiji OGAWA, Katsuari KAMEI, Kazuo INOUE
Article type: Article
2000 Volume 12 Issue 4 Pages
493-500
Published: August 15, 2000
Released on J-STAGE: January 07, 2018
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Kumiko IKUTA
Article type: Article
2000 Volume 12 Issue 4 Pages
501-506
Published: August 15, 2000
Released on J-STAGE: January 07, 2018
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Masahiro INUIGUCHI, Masaaki IDA
Article type: Article
2000 Volume 12 Issue 4 Pages
507-514
Published: August 15, 2000
Released on J-STAGE: January 07, 2018
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Yuichi INOUE
Article type: Article
2000 Volume 12 Issue 4 Pages
515-517
Published: August 15, 2000
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Kazutaka UMAYAHARA
Article type: Article
2000 Volume 12 Issue 4 Pages
518-520
Published: August 15, 2000
Released on J-STAGE: January 07, 2018
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Isao HAYASHI
Article type: Article
2000 Volume 12 Issue 4 Pages
521-524
Published: August 15, 2000
Released on J-STAGE: January 07, 2018
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Isao HAYASHI, Toshiro KUBOTA
Article type: Article
2000 Volume 12 Issue 4 Pages
525-527
Published: August 15, 2000
Released on J-STAGE: January 07, 2018
JOURNAL
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[in Japanese]
Article type: Article
2000 Volume 12 Issue 4 Pages
528-
Published: August 15, 2000
Released on J-STAGE: January 07, 2018
JOURNAL
FREE ACCESS
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[in Japanese]
Article type: Article
2000 Volume 12 Issue 4 Pages
528-
Published: August 15, 2000
Released on J-STAGE: January 07, 2018
JOURNAL
FREE ACCESS
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[in Japanese]
Article type: Article
2000 Volume 12 Issue 4 Pages
529-
Published: August 15, 2000
Released on J-STAGE: January 07, 2018
JOURNAL
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[in Japanese]
Article type: Article
2000 Volume 12 Issue 4 Pages
530-
Published: August 15, 2000
Released on J-STAGE: January 07, 2018
JOURNAL
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[in Japanese]
Article type: Article
2000 Volume 12 Issue 4 Pages
530-
Published: August 15, 2000
Released on J-STAGE: January 07, 2018
JOURNAL
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Masato SASAKI, Mitsuo GEN
Article type: Article
2000 Volume 12 Issue 4 Pages
531-538
Published: August 15, 2000
Released on J-STAGE: January 07, 2018
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In this paper, a hybridized genetic algorithm-based method for solving bicriteria knapsack problem with GUB (generalized upper bounding) structure is introduced. In this hybridized genetic algorithm, we propose the new chromosome representation which represents the GUB structure simply and effectively at a time. The proposed chromosome representation can hold the GUB structure in spite of carrying out the genetic operations. Further, the number of gene necessary to represent is much smaller than the chromosome representation based on 0-1 variables, so the proposed chromosome representation is advantageous over computation efficiency and memory required especially for large scale real world problems. Also, by introducing the hybrid genetic algorithm that makes use of the peculiarity of the GUB structure, the proposed approach is efficient in finding solution. That is, in each GUB constraint, the decision variables are ranked based on efficiency index and integrated into the process which improves the solution by ranking in genetic algorithm. Therefore, by the proposed approach, the solution can search solution efficiently. Further, to demonstrate the effectiveness of the proposed approach, a large scale reliability optimization problem is introduced for a numerical example.
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Shigenori TANAKA, Ichizou MIKAMI, Tatsuya HIWATASHI, Satoshi KUBOTA
Article type: Article
2000 Volume 12 Issue 4 Pages
539-551
Published: August 15, 2000
Released on J-STAGE: January 07, 2018
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The loosening of high-strength bolts in spliced joints of steel bridges has been founded during their inspection and maintenance. High-strength bolts can become loose if inadequate tightening torque was applied to them during the construction of bridges. or bridges in service may present some high-strength bolts loosened naturally with the passage of time. However, the method that can satisfy both work efficiency and inferring accuracy was not developed. In the present paper, the new method for inferring axial force of high-strength bolts was developed using neural network. The system to infer axial forces from the reaction and acceleration waveforms collected by the automatic looseness detector was built based on a neural network with the faculty of pattern recognition. First, the number of waveform data to be given to the neural network, the normalization and smoothing methods of waveform data were tested. Second, for practical use of the system, the relations between the arrangement and length of bolts, the thickness of web plates and spliced plates, and so on. As a result, the system that infer both the installed axial force in construction and the residual axial force in service of medium and small sized steel bridges was established.
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Kazutaka UMAYAHARA, Sadaaki MIYAMOTO
Article type: Article
2000 Volume 12 Issue 4 Pages
552-561
Published: August 15, 2000
Released on J-STAGE: January 07, 2018
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This paper considers the problem of detecting local linear substructures of a system in a high-dimensional data space by applying a fuzzy clustering technique. A problem in the adaptive method is pointed out. Namely, the value of the objective function does not have the monotonically decreasing property in the adaptive method. A new clustering method using an objective function with regularization of dimensional coefficients is proposed, whereby the monotonically decreasing property is guaranteed. In this paper, additive regularization using entropy, as well as the standard regularization by Bezdek, is studied in order to regularize membership values and dimensional coefficients. Illustrative examples are shown.
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Masatoshi SAKAWA, Kosuke KATO, Toshihiro SHIBANO, Kimihiko HIROSE
Article type: Article
2000 Volume 12 Issue 4 Pages
562-569
Published: August 15, 2000
Released on J-STAGE: January 07, 2018
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In this paper, for multidimensional integer knapsack problems we propose an approximate solution method through genetic algorithms which have recently attracted considerable attention in a number of fields as a methodology for optimization, adaptation and learning. For the multidimensional integer knapsack problems, M. Sakawa et al. proposed approximate solution methods through genetic algorithms using ringed double string representation or triple string representation, but more development and improvement are desired to them. Thus, in this paper, we propose a genetic algorithm using double string representation based on a solution for the corresponding continous relaxation problem to improve the accuracy or precision of solutions. Furthermore, the efficiency and effectiveness of the proposed method will be shown through various numerical experiments.
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Hugang HAN, Shuta MURAKAMI
Article type: Article
2000 Volume 12 Issue 4 Pages
570-577
Published: August 15, 2000
Released on J-STAGE: January 07, 2018
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Recently various adaptive fuzzy control schemes have been proposed to deal with nonlinear systems with poorly understood dynamics by using the parameterized fuzzy approximator. However, all of the adaptive fuzzy control systems have been designed for a continue-time system, but actually it is realized by discrete-time control system where computers are the manipulators. So there has existed a gap between the design and realized control system. The goal of this paper is to design a discrete-time adaptive fuzzy control system. The adaptive laws to adjust parameters in the system will be developed based on Lyapunov synthesis approach. It is shown the proposed fuzzy adaptive controller guarantees tracking error, between outputs of considered system and desired values, to be asymptotically in decay.
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Sadaaki MIYAMOTO, Kazutaka UMAYAHARA, Takeshi NEMOTO, Osamu TAKATA
Article type: Article
2000 Volume 12 Issue 4 Pages
578-587
Published: August 15, 2000
Released on J-STAGE: January 07, 2018
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This paper proposes an algorithm of fuzzy c-regression based on least absolute deviations. Theoretical properties of the algorithm and the solutions are moreover investigated. Objective functions for the standard c-regression as well as the regularization using an entropy term are studied. The calculation of the regression coefficients is reduced to the solution of a set of linear programming problems. Convergence of the alternative algorithm of the fuzzy c-regression is proved and theoretical properties of the classification functions are observed. Numerical examples show effectiveness of the present method of least absolute deviations.
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2000 Volume 12 Issue 4 Pages
588-591
Published: August 15, 2000
Released on J-STAGE: January 07, 2018
JOURNAL
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