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Self-organizing Relationship (SOR) Network with Fuzzy Inference Based Evaluation and Its Application to Trailer-Truck Back-Up Control

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Neural Information Processing (ICONIP 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3316))

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Abstract

In this paper, the self-organizing relationship (SOR) network with fuzzy inference based evaluation is proposed. The SOR network can extract a desired I/O relationship using I/O vector pairs and their evaluations. The evaluations can be given by a user or calculated by the evaluation function. However, in many applications, it is difficult to calculate the evaluation using simple functions. It is effective to employ fuzzy inference for evaluating the I/O vector pairs. The proposed system is applied to design the trailer-truck back-up controller, and experimental result is easily realized with some fundamental fuzzy if-then rules.

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References

  1. Kohonen, T.: Self-organizing formation of topologically correct feature map. Biol. Cybern. 43, 59–69 (1982)

    Article  MATH  MathSciNet  Google Scholar 

  2. Kohonen, T.: Self-organizing maps. Springer, Heidelberg (1995)

    Google Scholar 

  3. Lippmann, R.P.: Pattern Classification Using Neural Networks. IEEE Communication Magazine 27(11), 47–50 (1989)

    Article  Google Scholar 

  4. Tokutaka, H., Fujimura, K., Iwamoto, K., Kishida, S., Yoshihara, K.: Application of Self-Organizing Maps to a Chemical Analysis. In: Proc. of Int. Joint Conf. on Neural Information Processing, vol. 2, pp. 1318–1321 (1997)

    Google Scholar 

  5. Yamakawa, T., Horio, K.: Self-organizing relationship (SOR) network. IEICE Trans. on Fundamentals E82-A, 1674–1678 (1999)

    Google Scholar 

  6. Horio, K., Yamakawa, T.: Adaptive Self-Organizing Relationship Network and Its Application to Adaptive Control. In: Proc. of the 6th Int. Conf. on SoftComputing and Information/Intelligent Systems (IIZUKA 2000), pp. 299–304 (2000)

    Google Scholar 

  7. Nguyen, D., Widrow, B.: The truck backer-upper: an example of self-learning in neural nerwork. In: Proc. of IJCNN 1989, pp. 357–363 (1989)

    Google Scholar 

  8. Kong, S.G., Kosko, B.: Adaptive fuzzy-systems for backing-up a truck-andtrailer. IEEE Trans. on Neural Networks 3(2), 211–223 (1992)

    Article  Google Scholar 

  9. Tanaka, K., Sano, M.: A robust stabilization problem of fuzzy control systems and its application to backing up control of a truck-trailer. IEEE Trans. on Fuzzy Systems 2(2), 119–133 (1994)

    Article  Google Scholar 

  10. Mizumoto, M.: Fuzzy controls by product-sum-gravity method. Advancement of Fuzzy Theory and Systems in China and Japan, International Academic Publishers, c1.1-c.1.4 (1990)

    Google Scholar 

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© 2004 Springer-Verlag Berlin Heidelberg

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Koga, T., Horio, K., Yamakawa, T. (2004). Self-organizing Relationship (SOR) Network with Fuzzy Inference Based Evaluation and Its Application to Trailer-Truck Back-Up Control. In: Pal, N.R., Kasabov, N., Mudi, R.K., Pal, S., Parui, S.K. (eds) Neural Information Processing. ICONIP 2004. Lecture Notes in Computer Science, vol 3316. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30499-9_56

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  • DOI: https://doi.org/10.1007/978-3-540-30499-9_56

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23931-4

  • Online ISBN: 978-3-540-30499-9

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