Investigating the development of digital patterns for customized apparel

Yang, Yunchu; Zhang, Weiyuan

doi:10.1108/09556220710741632

Cited by 48 publications

(31 citation statements)

References 9 publications

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“…Therefore, many researchers began to seek intelligent methods for GPD. In [1], an overview of the area of digital pattern developing for customized garment is given. In the literature, there are five types of intelligent methods in GPD.…”

Section: A Copy Intelligent Methods In Garment Designmentioning

confidence: 99%

A Hybrid System Based on Neural Network and Immune Co-Evolutionary Algorithm for Garment Pattern Design Optimization

Hu¹

2009

JCP

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The purpose of this study is to develop a system to utilize the successful experiences and help the beginners of garment pattern design (GPD) by optimization methods. A hybrid algorithm (NN-ICEA) based on Neural Network (NN) and immune co-evolutionary algorithm (ICEA) to predict the fit of the garments and search optimal sizes. ICEA takes NN as fitness function and procedures including clonal proliferation, hyper-mutation and co-evolution search the optimal size values. Then, a series of experiments with a dataset of 450 pieces of garments are conducted to demonstrate the prediction and optimization capabilities of NN-ICEA. In the comparative studies, NN-ICEA is compared with NN-GA to show the value of immune inspired operators. Four types of GPD methods are summarized and compared. Moreover, the hybrid system for general features of garment is discussed. The fit prediction based on NN can achieve the high accuracy with the error rate less than 0.2. The size optimization based on ICEA works well when number of the missing sizes is less than 1/3 of the total size number. The research is a feasible and effective attempt aiming at a valuable problem and provides key algorithms for fit prediction and size optimization. The algorithms can be incorporated into garment CAD system.

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Section: A Copy Intelligent Methods In Garment Designmentioning

confidence: 99%

A Hybrid System Based on Neural Network and Immune Co-Evolutionary Algorithm for Garment Pattern Design Optimization

Hu¹

2009

JCP

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“…1 shows a three-layer neural network model for pattern-making process. The construction of ANN model can be outlined by following procedure [11] x Data preparation. In the phase, a large amount of relevant data of the patterns is gained by means of either manual preparing or computer generation.…”

Section: Networkmentioning

confidence: 99%

A survey on pattern-making technologies in Garment CAD

Wan

2013

IEEE Conference Anthology

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Since interactive pattern-making technique in Garment CAD has its inherent limitation, some advanced pattern-making ones are intensively studied. This paper reviews state-of-art pattern-making techniques, including pattern generation based on artificial neural network pattern flattening technique from 3D human or garment model and parametric pattern-making technique. In each technique, basic principles, characteristic and application are systematically discussed and commented. In first technique, the model of artificial neural network is constructed to simulate a patternmaking process. Pattern flattening technique is one of the key techniques of 3D GCAD system, geometrical and physical pattern flattening approaches are presented in this technique. Variant programming, macro definition, parametric model based on sequence and dimensional constraints, parametric model based on dimensional and geometric constraints are included in parametric pattern-making technique, parametric model based on dimensional and geometric constraints is considered as a promising one. Keywords-Garment CAD; pattern-making technique; artificial neural network; parametric pattern-making model; pattern flatteningI.

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“…al. [7] , there are two main ways to implementing the purpose. The first way is to modify a ready-to-wear pattern using a certain grading rule.…”

Section: Introductionmentioning

confidence: 99%