Soft Computing

May 1st, 2015
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What is Soft Computing ? (adapted from L.A. Zadeh) Lecture 1 What is soft computing Techniques used in soft computing • Soft computing differs from conventional (hard) computing in that, unlike hard computing, it is tolerant of imprecision, uncertainty, partial truth, and approximation. In effect, the role model for soft computing is the human mind.

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Soft ComputingWhat is Soft Computing ? (adapted from L.A. Zadeh) Lecture 1 What is soft computing Techniques used in soft computing Soft computing differs from conventional (hard) computing in that, unlike hard computing, it is tolerant of imprecision, uncertainty, partial truth, and approximation. In effect, the role model for soft computing is the human mind.12What is Hard Computing? Hard computing, i.e., conventional computing, requires a precisely stated analytical model and often a lot of computation time. Many analytical models are valid for ideal cases. Real world problems exist in a non-ideal environment. 3What is Soft Computing? (Continued) The principal constituents, i.e., tools, techniques, of Soft Computing (SC) are Fuzzy Logic (FL), Neural Networks (NN), Support Vector Machines (SVM), Evolutionary Computation (EC), and Machine Learning (ML) and Probabilistic Reasoning (PR)4Premises of Soft Computing The real world problems are pervasively imprecise and uncertain Precision and certainty carry a costGuiding Principles of Soft Computing The guiding principle of soft computing is: Exploit the tolerance for imprecision, uncertainty, partial truth, and approximation to achieve tractability, robustness and low solution cost.56Hard Computing Premises and guiding principles of Hard Computing are Precision, Certainty, and rigor.Implications of Soft Computing Soft computing employs NN, SVM,

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