Email this article 
Open Access
Subscription or Fee Access
Soft Computing
Abstract
Soft computing is an evolving collection of methodologies, which aims to exploit tolerance for imprecision uncertainty, and partial truth to achieve robustness, tractability, and low cost. It can be a very attractive alternative to a purely digital system, but there are many traps waiting for researches trying to apply this new exciting technology. Software computing provides attractive opportunity to represent the ambiguity in human thinking with real life uncertainty. Fuzzy logic, Neural Networks, and Evolutionary Computation are the core methodologies of soft computing. For nonlinear processing both neural networks and fuzzy systems can be used.
Keywords
References
http://www.soft-computing.de/def.html
https://rgpv8thsem.wordpress.com/2011/04/20/hard-computing-vs-soft-computing/
Digital Image-processing fundaments are given in this website: http://www.ph.tn.tudelft.nl/courses/FIP/frames/fip. html
https://www.classle.net/#!/classle/content-page/soft-computing-and-its-importance/
http://shodhganga.inflibnet.ac.in/bitstream/10603/11748/9/09_chapter_03.pdf
X. M. Gao, X. Z. Gao, J. M. A. Tanskanen, and S. J. Ovaska (1997), “Power prediction in mobile communication systems using an optimal neural-network structure,” IEEE Trans. Neural Networks
C.-W. Liu, M.-C. Su, S.-S. Tsay, and Y.-J. Wang (1999), “Application of a novel fuzzy neural network to real-time transient stability swings prediction based on synchronized phasor measurements,” IEEE Trans. Power Syst
Sivakumar Ganesan (2004). Soft Computing Techniques: Theory and Application For Pattern Classification
http://www.slideshare.net/ankush281290/introduction-to-soft-computing
http://shodhganga.inflibnet.ac.in/bitstream/10603/34784/10/10_chapter1.pdf
Refbacks
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.