Soft computing in fibrous materials engineering

Abstract

Soft computing is a cluster of modelling and optimisation techniques which mimics the behaviour of biological systems. Artificial neural network (ANN), fuzzy logic (FL) and genetic algorithms (GA) are three main constituents of soft computing. In recent years, soft computing systems have been successfully used in every discipline of science, technology and engineering. Fibrous materials possess a unique combination of characteristics as they are strong, flexible and light-weight. Therefore, fibrous materials are gaining increased attention with time from the materials scientists and engineers. When fibrous materials are used for technical applications, the requirement in terms of functional properties becomes more important than the aesthetics. In certain cases, it becomes imperative to get an idea about the properties of the fibrous materials before their manufacturing. As the fibrous materials have inherent variability, estimation of their properties by mathematical models often yields a very high prediction error. Soft computing systems present the potential solutions for the modelling and optimisation of fibrous materials. This monograph presents a compendium of researches on the application of soft computing techniques in fibrous materials modelling, optimisation and engineering.

Keywords:

• artificial neural network
• fibrous materials
• fuzzy logic
• genetic algorithm
• soft computing

Notes

¹Part of Sections 2.3 and 2.6 have been reproduced from the author's contribution ‘Adaptive neurofuzzy system in yarn modelling’ in Soft Computing in Textile Engineering, Woodhead Publishing, UK.