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This system combines clothes components and fabric pattern set, using the interactive genetic algorithm and laws based on fashion design.
Ogata and Onisawa (2007) have presented a fashion design support system, using the interactive genetic algorithm, which allows applying users' opinions.
The research, therefore, tries to present a computer aided fashion design system, which can employ various types of fabrics designed as a set by using the interactive genetic algorithm and considering consumer's taste in fashion set design.
The first dimension is to technically discuss gene compositions within chromosome framework, performed by laws of fashion design art and by a software designer (using the genetic algorithm); the second is to use the customer's opinions to increase the productivity of clothes designed before producing and supplying them to market, using the interactive genetic algorithm.
Using the interactive genetic algorithm, Mok et al. (2012) have presented a fashion sketch design system to accelerate the design process: (1) a design model based on design knowledge to describe the features of the fashion product using developed parameters; (2) a database based on suggesting a fashion design method to define the elements of a general style; and a multi-stage sketch design motor.
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For this purpose, niching methods [21] were used in the interactive genetic algorithm.
To evaluate the proposed method, 15 users were asked to perform the cover design process separately using the simple interactive genetic algorithm, multi-stage interactive genetic algorithm, and the proposed algorithm.
Figure 4 Capturing data using the interactive wall-sized whiteboard.
Clinicians randomised to using the interactive booklet will receive online training in its use.
In the proposed method, the candidate elimination algorithm is used in combination with the interactive genetic algorithm in order to identify the user preference in scoring the designs and to prevent the evaluation of inappropriate solutions (i.e., designs which do not match user preference) by user.
Different studies have used different interactive algorithms, particularly the interactive genetic algorithm, for design in different areas.
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