Intelligent fashion styling using genetic search and neural classification

Arzu Vuruskan (Department of Fashion and Textile Design, Izmir University of Economics, Izmir, Turkey.)
Turker Ince (Department of Electrical and Electronics Engineering, Izmir University of Economics, Izmir, Turkey.)
Ender Bulgun (Department of Fashion and Textile Design, Izmir University of Economics, Izmir Turkey.)
Cuneyt Guzelis (Department of Electrical and Electronics Engineering, Izmir University of Economics, Izmir, Turkey.)

International Journal of Clothing Science and Technology

ISSN: 0955-6222

Publication date: 20 April 2015

Abstract

Purpose

The purpose of this paper is to develop an intelligent system for fashion style selection for non-standard female body shapes.

Design/methodology/approach

With the goal of creating natural aesthetic relationship between the body shape and the shape of clothing, garments designed for the upper and lower body are combined to fit different female body shapes, which are classified as V, A, H and O-shapes. The proposed intelligent system combines genetic algorithm (GA) with a neural network classifier, which is trained using the particle swarm optimization (PSO). The former, called genetic search, is used to find the optimal design parameters corresponding to a best fit for the desired target, while the task of the latter, called neural classification, is to evaluate fitness (goodness) of each evolved new fashion style.

Findings

The experimental results are fashion styling recommendations for the four female body shapes, drawn from 260 possible combinations, based on variations from 15 attributes. These results are considered to be a strong indication of the potential benefits of the application of intelligent systems to fashion styling.

Originality/value

The proposed intelligent system combines the effective searching capabilities of two approaches. The first approach uses the GA for identifying best fits to the target shape of the body in the solution space. The second is the PSO for finding optimal (with respect to training mean-squared error) weight and threshold parameters of the neural classifier, which is able to evaluate the fitness of successively evolved fashion styles.

Keywords

Citation

Vuruskan, A., Ince, T., Bulgun, E. and Guzelis, C. (2015), "Intelligent fashion styling using genetic search and neural classification", International Journal of Clothing Science and Technology, Vol. 27 No. 2, pp. 283-301. https://doi.org/10.1108/IJCST-02-2014-0022

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Publisher

:

Emerald Group Publishing Limited

Copyright © 2015, Emerald Group Publishing Limited

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