Soft Computing in Textile Engineering (Woodhead Publishing by Abhijit Majumdar

By Abhijit Majumdar

Gentle computing is an rising sector of inter-disciplinary study. It refers to a suite of computational options which research, version and learn advanced phenomena. As many cloth engineering difficulties are inherently advanced in nature, gentle computing strategies have usually supplied optimal recommendations to those situations. even supposing gentle computing has a number of features, it typically revolves round 3 innovations together with: man made neural networks, fuzzy good judgment and genetic algorithms. The publication is split into 5 elements, protecting the full technique of fabric creation, from fiber manufacture to garment engineering. those contain tender computing ideas in yarn manufacture and modeling, cloth and garment manufacture, fabric houses and functions and fabric caliber overview.

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4, pp. 1016–1031, 2007. [53] M. Banerjee, S. Mitra and S. K. Pal, ‘Rough fuzzy MLP: Knowledge encoding and classifications’, IEEE Trans. Neural Networks, Vol. 9, pp. 1203–1216, 1998. [54] Sankar Kumar Pal, Lech Polkowski and Andrej Skowron, Rough-Neural Computing: Techniques for Computing with Words’, Springer-Verlag, Berlin, 2004. indd 24 10/21/10 5:12:36 PM 2 Artificial neural networks in materials modelling M. M u r u g a n a n t h, Tata Steel, India Abstract: This chapter discusses the development of artificial neural networks (ANNs) and presents various models as illustration.

9–12]. indd 12 10/21/10 5:12:29 PM Introduction to soft computing techniques 13 Rr: IF x1 is Ar1 AND x2 is Ar 2 AND … AND xn is Arn ,   THeN yr = ar0 + ar1x1 + … + arn xn. 9 m S tj S tj j=1 j=1 where t i = Ÿ [m Ai 1 (x1 ) m Ai 2 (x2 ) … m Ain (xxn )].    Fuzzy logic techniques are increasingly being used in various applications [10–12] like classification and clustering, control, system identification, cognitive mapping, etc. 4 Neural networks The human brain has a mass of about 30 lb and a volume of 90 cubic inches, and consists of about 90 billion cells.

When the universe is a collection of a finite number of ordered discrete points, the corresponding fuzzy set may be represented by m A (xn ) ¸ Ï n m A (xi ) ¸ Ïm A (x1 ) m A (x2 ) A=Ì  +  +…+  = S  x2 xn ˝˛ ÌÓÔi =1 xi ˝˛Ô Ó x1 where the summation indicates aggregation of elements. 4 (a) Membership representation for crisp sets; (b) degree of membership representation for fuzzy sets. indd 11 10/21/10 5:12:27 PM 12 ∑ Soft computing in textile engineering The intersection A and B (A « B) fi m A«B ( x ) = Ÿ (m A (x ), m B ((xx ))         ∀x Œ X, where Ÿ denotes minimum.

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