Nothing Special   »   [go: up one dir, main page]

Skip to main content

An introduction to soft computing — A tool for building intelligent systems

  • Chapter
  • First Online:
Software Agents and Soft Computing Towards Enhancing Machine Intelligence

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1198))

Abstract

“The essence of soft computing is that unlike the traditional, hard computing, soft computing is aimed at an accommodation with the pervasive imprecision of the real world. Thus, the guiding principle of soft computing is: ‘...exploit the tolerance for imprecision, uncertainty and partial truth to achieve tractability, robustness, low solution cost and better rapport with reality’. In the final analysis, the role model for soft computing is the human mind.” [1]

In this paper terms associated with soft computing are defined and its main components are introduced. It is argued, using a number of practical applications, that the hybrid approach of soft computing can provide a methodology for increasing machine intelligence.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Zadeh L A: ‘The roles of fuzzy logic and soft computing in the conception, design and deployment of intelligent systems', BT Technol J, 14, No 4, pp 32–36 (October 1996).

    Google Scholar 

  2. Uhr L and Honavar V: ‘Introduction', in: ‘Artificial Intelligence and Neural Networks — Steps Toward Principled Integration', Academic Press (1994).

    Google Scholar 

  3. Zadeh L A: ‘Fuzzy Logic, Neural Networks and Soft Computing', Comm of ACM, 37, No 3, pp 77–84 (March 1994).

    Google Scholar 

  4. Mamdani E H: ‘Towards Soft Computing', Proc BCS Expert Systems Conference, Cambridge (December 1995).

    Google Scholar 

  5. Kosko B: ‘Neural Networks and Fuzzy Systems — A Dynamical Systems Approach to Machine Intelligence', Prentice Hall (1992).

    Google Scholar 

  6. Horstkotte E: http://www.quadralay.com/www/Fuzzy/Fuzzy.html

    Google Scholar 

  7. Munakata T and Jani Y: ‘Fuzzy Systems: An Overview', Comm of ACM, 37, No 3, pp 69–76 (March 1994).

    Google Scholar 

  8. Zadeh L A: ‘Soft Computing and Fuzzy Logic', IEEE Software, 11, No 6, pp 48–58 (1994).

    Google Scholar 

  9. Barto A, Sutton R and Anderson C: ‘Neuro-like Adaptive Elements that can Solve Difficult Control Problems', IEEE Tran on Systems, Man and Cybernetics, No 13 (1983).

    Google Scholar 

  10. Dayhoff J: ‘Neural Network Architectures', Van Nostrand Reinhold (1990).

    Google Scholar 

  11. Goldberg D E: ‘Genetic and Evolutionary Algorithms Come of Age', Comm of ACM, 37, No 3, pp 113–119 (March 1994).

    Google Scholar 

  12. Fukura T: ‘Fuzzy-neuro-GA Based Intelligent Robotics', in: ‘Computational Intelligence Imitating Life', IEEE Press, pp 352–363 (1994).

    Google Scholar 

  13. Fox J: ‘Towards a reconciliation of fuzzy logic and standard logic', Int J of Man Machine Studies, 15, pp 213–220 (1981).

    Google Scholar 

  14. Bezdek J C: ‘What is Computational Intelligence', in: ‘Computational Intelligence Imitating Life', IEEE Press, pp 1–12 (1994).

    Google Scholar 

  15. Carpenter G, Grossberg S, Markuzon N, Reynold H J and Rosen D B: ‘Fuzzy ARTMAP: A Neural Network Architecture for Incremental Supervised Learning of Analogue Multi-dimensional Maps', IEEE Tran on Neural Networks, 3, No 5, pp 698–713 (1992).

    Google Scholar 

  16. Tsao E C K, Bezdek J C and Pal N R: ‘Image Segmentation Using Fuzzy Clustering Networks', in North American Fuzzy Information Processing, pp 98–107 (1992).

    Google Scholar 

  17. Wang L X: ‘Training Fuzzy Logic Systems Using Nearest Neighbourhood Clustering', Manuscript (1992).

    Google Scholar 

  18. Asakawa K and Takagi H: ‘Neural Networks in Japan', Comm of ACM (March 1994).

    Google Scholar 

  19. Medsker A R: ‘Hybrid Intelligent Systems', Kluwer Academic Publishers (1995).

    Google Scholar 

  20. Berenji H R: ‘Fuzzy Systems That Can Learn', in: ‘Computational Intelligence Imitating Life', IEEE Press, pp 23–30 (1994).

    Google Scholar 

  21. NEFCON: http://sol.ibr.cs.tu-bs.de/ibr/projects/nefcon/

    Google Scholar 

  22. Hitachi News Release: ‘Neuro and fuzzy logic automatic washing machine and fuzzy logic dryer', No. 91-024 (February 1991).

    Google Scholar 

  23. Sanyo News Release: ‘Electric fan series in 1991', (March 1991).

    Google Scholar 

  24. Takagi H: ‘Co-operative system of neural networks and fuzzy logic and its application to consumer products', in: ‘Industrial Applications of Fuzzy Control and Intelligent Systems', IEEE Press (1994).

    Google Scholar 

  25. Nakajima M, Okada T, Hattori S and Morroka Y: ‘Application of pattern recognition and control techniques to shape control of the rolling mill', Hitachi Review, 75, No 2 (1993).

    Google Scholar 

  26. Takagi H: 'survey of fuzzy logic applications in image processing equipment', in: ‘Industrial Applications of Fuzzy Control and Intelligent Systems', IEEE Press (1995).

    Google Scholar 

  27. Hellendoorn H, Metternich W, Nissel M, Seising R and Thomas C: ‘Traffic management for broadband networks with fuzzy logic — call admission control and usage parameter control', Proceedings of EUFIT'96 (September 1996).

    Google Scholar 

  28. Baldwin J and Martin T: ‘Basic concepts of fuzzy logic data browser with applications', in Nwana H and Azarmi N (Eds): ‘Software Agents and Soft Computing: Towards Enhancing Machine Intelligence', Springer Verlag, Berlin (December 1996).

    Google Scholar 

  29. Zadeh L A: ‘Foreword', in Medsker L R: ‘Hybrid Intelligent Systems', Kluwer Academic Publishers (1995).

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Hyacinth S. Nwana Nader Azarmi

Rights and permissions

Reprints and permissions

Copyright information

© 1997 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Azvine, B., Azarmi, N., Tsui, K.C. (1997). An introduction to soft computing — A tool for building intelligent systems. In: Nwana, H.S., Azarmi, N. (eds) Software Agents and Soft Computing Towards Enhancing Machine Intelligence. Lecture Notes in Computer Science, vol 1198. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-62560-7_46

Download citation

  • DOI: https://doi.org/10.1007/3-540-62560-7_46

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-62560-5

  • Online ISBN: 978-3-540-68079-6

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics