Developing a New Suit Sizing System Using Neural Network

Abstract

Manufacturing garments has the highest added value in the textile industry. Presently, most sizing systems are outdated, so each country needs to develop a new sizing system for its people. The main goal of this work was to present the new sizing chart for Iranian male suites using an artificial neural network. 10 effective sizing variables for producing suits are determined, and then all different body sizes are clustered using the Kohonen neural network. Aggregate loss is used as a tool to measure fitness of the newly obtained sizing chart. The results have a good coverage on Iranian body types, and could be used as a reference for apparel companies in Iran and other companies which produce suit for Iranian males.

Predicting the Bending Rigidity and Formability of Plasma-Treated Spunbond Nonwoven Fabrics Using Artificial Intelligence

“…Artificial intelligence is currently used in numerous fields to find the nonlinear and complex relationships between the independent and dependent parameters of engineering systems. In the textile industry, many works have been published reporting the success of using artificial intelligence to predict or optimize the physical and mechanical properties of textiles [10][11][12][13][14][15][16][17][18][19]. However, to the best of the authors' knowledge, no paper has been published regarding the prediction of bending rigidity and formability under the influence of plasma treatment.…”

Development of a Military Uniform Size System Using Hybrid Support Vector Clustering with a Genetic Algorithm

“…Hsu [24] proposed an Artificial Neural Network (ANN)-based data mining framework to generate useful patterns for developing standard size charts. For Iranian male suits, Vadood et al [25] presented a novel sizing chart by artificial neural network approaches. To cluster different body sizes, the Kohonen neural network was adopted with ten sizing parameters.…”