Open Access Open Access  Restricted Access Subscription or Fee Access

Soft Computing: A Survey

Lukesh M. Barapatre, Anand Sharma

Abstract


Soft Computing is the fusion of methodologies that were designed to model and enable solutions to real world problems, which are not modeled or too difficult to model, mathematically.

A grouping of methods that works synergistically with soft computing method provides one or another Real-life flexible information processing capacity to handle ambiguous situations. Its purpose is to use tolerance impurities, Uncertainty, and partial truth about the ability to detect logic, in order to achieve stability and cost principles with a view to resolving ambiguous or accurately estimated, preferably, the method of calculation leads to an acceptable solution, to devise problem formulation.

Soft Computing (SC) reflects the fact that the purpose of computing represents a significant shift in the human mind. Computers store and uncertain and lacking in categoricity widely remarkable ability to process information that is imprecise & uncertain.

This time, Soft Computing (SC) of the major components: are: Fuzzy Systems (FS), including Fuzzy Logic (FL); Evolutionary Computation (EC), including Genetic Algorithms (GA); Neural Networks (NN), including Neural Computing (NC); Machine Learning (ML); and Probabilistic Reasoning (PR). In this paper we focus on fuzzy methodologies and fuzzy systems, as they bring basic ideas to other SC methodologies.


Keywords


Soft Computing, Machine Learning, Fuzzy Logic

Full Text:

PDF

References


"Europe Gets into Fuzzy Logic" (Electronics Engineering Times, Nov. 11, 1991).

"Fuzzy Sets and Applications: Selected Papers by L.A. Zadeh", ed. R.R. Yager et al. (John Wiley, New York, 1987).

"U.S. Loses Focus on Fuzzy Logic" (Machine Design, June 21, 1990).

Koza, J.R.,”Genetic Programming II”, A Bradford Book, MIT Press, Cambridge, 1994.

Shanahan, J.G., Soft Computing for Knowledge Discovery, Kluwer Acad.Publ., Boston /Dordrecht /London, 2000

Barber, J. C. 1995. "Genetic Algorithms as Tools for Optimization," Risks and Rewards, December.

Bishop, C. M. 1995. Neural Networks for Pattern Recognition. Clarendon Press.

Neural Network Learning and Expert Systems,Cambridge, MA:MIT Press, 1994.

I. A. Taha and J. Ghosh, “Symbolic interpretation of artificial neural networks,”IEEE Trans. Knowl. Data Eng., vol. 11, pp. 448–463, 1999.

Abraham A (2004) Meta-Learning Evolutionary Artificial Neural Networks, Neurocomputing Journal, Elsevier Science, Netherlands, 56c, pp. 1–38

Ahuja RK, Orlin JB, and Tiwari A (2000) A greedy genetic algorithm for the quadratic assignment problem, Computers and Operations Research, 27, 917–934

Aruldoss AVT and Ebenezer JA (2004) Hybrid PSO-SQP for economic dispatch with valve-point effect, Electric Power Systems Research, 71(1), pp. 51–59

R. Bellmann and L. Zadeh, Decision making in fuzzy environment. Man-agement Science17 (4), 1970, 141-164.

C. Bertoluzza and A. Bodini, A new proof of Nguyen’s compatibility theorem in a more general context. Fuzzy Sets and Systems95 (1998) 99-102

J. Kennedy and R. Eberhart, “Particle swarm optimization.” Proc. IEEE International Conf. on Neural Networks (Perth, Australia), IEEE Service Center, Piscataway, NJ, 1995 (in press)

T. Baeck, “Generalized convergence models for tournament and (mu,lambda)-selection.” Proc. of the Sixth International Conf on Genetic Algorithms, pp. 2-7, Morgan Kaufmann Publishers, San Francisco, CA, 1995

R. Eberhart and J. Kennedy, ”A new optimizer using particle swarm theory", Proc. 6th Int. Symp. Micro Machine and Human Science (MHS ',95), pp.39 -43 1995

J. Kennedy and R. Beernaert,”Particle swarm optimization", Proc. IEEE Int. Conf. Neural Networks, vol. 4, pp.1942 -1948 1995

E. Ozcan and C. K. Mohan, ”Particle swarm optimization: Surfing the waves", Proc. Congr. Evolutionary Computation (CEC 99), vol. 3, pp.1939 -1944 1999

J. Robinson, S. Sinton, and Y. Rahmat-Samii, "Particle swarm, genetic algorithm, and their hybrids: Optimization of a profiled corrugated horn antenna", IEEE Antennas Propagat. Soc. Int. Symp. Dig., vol. 1, pp.314 -317 2002

J. H. Holland,”Genetic algorithms", Scientific American, pp.66-721992

R. L. Haupt and S. E. Haupt, Practical Genetic Algorithms, 1998: Wiley


Refbacks

  • There are currently no refbacks.