Concepts of Soft Computing [electronic resource] : Fuzzy and ANN with Programming /

By:

Chakraverty, Snehashish [author.]

Contributor(s):

Material type: Text

TextPublisher: Singapore : Springer Nature Singapore : Imprint: Springer, 2019Edition: 1st ed. 2019Description: XXII, 195 p. 222 illus., 38 illus. in color. online resourceContent type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9789811374302

Subject(s):

Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification:

621.39 23
004.6 23

LOC classification:

TK7885-7895
TK5105.5-5105.9

Online resources:

Click here to access online

Contents:

Soft Computing -- Intervals -- Fuzzy Sets -- Fuzzy Numbers -- Fuzzy Relations -- Fuzzy Functions -- Fuzzy differentiation and integration -- Defuzzification -- Interval system of linear equations -- Interval eigenvalue problems.

In: Springer Nature eBookSummary: This book discusses soft computing, which provides an efficient platform to deal with imprecision, uncertainty, vagueness and approximation in order to attain robustness and reliable computing. It explores two major concepts of soft computing: fuzzy set theory and neural networks, which relate to uncertainty handling and machine learning techniques respectively. Generally, fuzzy sets are considered as vague or uncertain sets having membership function lying between 0 and 1, and ANN is a type of artificial intelligence that attempts to imitate the way a human brain works by configuring specific applications, for instance pattern recognition or data classification, through learning processes. The book also presents C/MATLAB programming codes related to the basics of fuzzy set, interval arithmetic and ANN in a concise, practical and adaptable manner along, with simple examples and self-validation unsolved practice questions in few cases.

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This book discusses soft computing, which provides an efficient platform to deal with imprecision, uncertainty, vagueness and approximation in order to attain robustness and reliable computing. It explores two major concepts of soft computing: fuzzy set theory and neural networks, which relate to uncertainty handling and machine learning techniques respectively. Generally, fuzzy sets are considered as vague or uncertain sets having membership function lying between 0 and 1, and ANN is a type of artificial intelligence that attempts to imitate the way a human brain works by configuring specific applications, for instance pattern recognition or data classification, through learning processes. The book also presents C/MATLAB programming codes related to the basics of fuzzy set, interval arithmetic and ANN in a concise, practical and adaptable manner along, with simple examples and self-validation unsolved practice questions in few cases.

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