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Problem Formalization and Problem Solving Approach based on Fusion Model

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Soft Computing as Transdisciplinary Science and Technology

Part of the book series: Advances in Soft Computing ((AINSC,volume 29))

Abstract

The quadrant for problem formalization is introduced based on problem definition and structure. Problem formalization has significant influence on not just for satisfying reasonable cost and performance but also conforming problem solving approach. Based on the quadrant, problem solving approach is discussed with considering the fusion model of human experts’ domain knowledge and field data. The fusion model plays an important role in problem solving stages of Learning and Execution. Auditory-based product inspection systems as real world problems are studied with considering problem formalization concepts and the fusion model.

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References

  1. Russell, S., and Norvig, P. (1995) The chapter 3 in “Artificial Intelligence — A Modern Approach,” Prentice Hall, Inc.

    Google Scholar 

  2. Kawaji, S., Matsunaga, N., and Arao, M. (1999) “Toward a Paradigm for Information Integrated Control Systems-the Control Theoretic View of Intelligent Control Technology,” Journal of Artificial Life and Robotics, Vol.3, No.4, pp.203–208.

    Article  Google Scholar 

  3. Kawaji, S. (2000) “A Control-Theoretic View of Intelligent Control,” Journal of Robotics and Mechatronics, Vol.12, No.6, pp.605–613.

    Google Scholar 

  4. Arao, M., Tashima, T., and Kawaji, S. (1998) “Flexible Intelligence Machine Controller and Its Application to Jacket Tank Temperature Control,” Proceedings of SMC’98, San Diego, pp.1376–1381

    Google Scholar 

  5. Bezdek, J.C. (1994) “What is Computational Intelligence?”, in Zurada, J.M., Marks II, R.J., and Ronbinson, C.J., eds., Computational Intelligence: Imitating Life, IEEE Press, Piscataway, NJ, pp. 1–11.

    Google Scholar 

  6. OMRON Corporation (2003), http://www.signarc.com

    Google Scholar 

  7. Inaba, H., Kojitani, K., and Nakajima, H. (2004) “Human Brain Work Autonomation,” No. 44, Vol.1, OMRON TECHNICS.

    Google Scholar 

  8. Taguchi, G., and Jugulum, R. (2002) “The Mahalanobis Taguchi Strategy: A Pattern Technology System,” John Wiley & Sons Inc.

    Google Scholar 

  9. Tax, D.M.J. (2001) “One-class classification-Concept-learning in the absence of counter-examples,” Ph.D. dissertation, Technische University. (http://www.ph.tn.tudelft.nl/~davidt/thesis.pdf)

    Google Scholar 

  10. Ovaska, S.J. eds.(2004) The chapter 1 in “Computationally Intelligent Hybrid Systems — The Fusion of Soft Computing and Hard Computing,” Wiley-Interscience.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Control Laboratory, OMRON Corporation, Keihanna Kakken City, 9-1 Kuzugawadai, Kizucho, Soraku-gun, Kyoto, 619-0283, Japan

    Hiroshi Nakajima, Kazuto Kojitani & Masaki Arao

  2. Faculty of Engineering, Kumamoto University, 40-1, Kurokami 2-chome, Kumamoto, 860-8555, JAPAN

    Shigeyasu Kawaji

Authors
  1. Hiroshi Nakajima
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  2. Kazuto Kojitani
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  3. Masaki Arao
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  4. Shigeyasu Kawaji
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Editor information

Editors and Affiliations

  1. Dept. of Computer Science, Oklahoma State University, North Greenwood Avenue 700, 74106, Tulsa, USA

    Ajith Abraham

  2. Dept. of Computer Science and Systems Engineering, Muroran Institute of Technology, Mizumoto-cho 27-1, 050-8585, Muroran, Hokkaido, Japan

    Yasuhiko Dote

  3. Dept. of Computational Science and Engineering, Nagoya University, Furo-cho, Chikusa-ku, 464-8601, Nagoya, Aichi-ken, Japan

    Takeshi Furuhashi

  4. Institut für Sicherheits-/Prüftechnik, Fraunhofer IPK Berlin, Pascalstr. 8-9, 10587, Berlin, Germany

    Mario Köppen

  5. Division of Complex Systems Technology Graduate School of Engineering, University of Hokkaido, N-13, W-8 060 KITA-KU, Sapporo, Japan

    Azuma Ohuchi

  6. PRESTO Japan Science & Technology Corp. GSSM, University of Tsukuba, 3-29-1 Otsuka, Bunkyo-ku, 12-0012, Tokyo, Japan

    Yukio Ohsawa

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© 2005 Springer-Verlag Berlin Heidelberg

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Nakajima, H., Kojitani, K., Arao, M., Kawaji, S. (2005). Problem Formalization and Problem Solving Approach based on Fusion Model. In: Abraham, A., Dote, Y., Furuhashi, T., Köppen, M., Ohuchi, A., Ohsawa, Y. (eds) Soft Computing as Transdisciplinary Science and Technology. Advances in Soft Computing, vol 29. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32391-0_44

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  • DOI: https://doi.org/10.1007/3-540-32391-0_44

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25055-5

  • Online ISBN: 978-3-540-32391-4

  • eBook Packages: EngineeringEngineering (R0)

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