Key Training Items Search of Manufacturing Assessment Based on TTQS and GA-SVM

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Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/38951

Title:	Key Training Items Search of Manufacturing Assessment Based on TTQS and GA-SVM
Authors:
Contributors:	Department of Information Engineering and Computer Science National Taichung University of Science and Technology Department of Leisure and Recreation Management Asia University National Changhua University of Education 休閒與遊憩管理學系
Keywords:	Training quality;TTQS;genetic algorithm;support vector machine
Date:	2013
Issue Date:	2013-07-26 06:36:19 (UTC+0)
Publisher:	Department of Information Engineering and Computer Science National Taichung University of Science and Technology Department of Leisure and Recreation Management Asia University National Changhua University of Education
Abstract:	In Taiwan, the Government designed a system called Taiwan Train Quali System (TTQS), which helps the enterprises to build up a quality control and training system for strengthening their competition and rising up the performance. In order to help the enterprises to focus on the important assessment items, there were some researchers combining genetic algorithm and support vector machine to be a GA-SVM algorithm to find the key training items of TTQS for the business growth. However, those researches were only for the analysis result of all industries, also they were not have further consideration about the characteristics of the individual industry, and the classification according as the turnover growth rates, which can not directly relate to the assessment result of TTQS. Thus, the proposed paper amended the analysis based on the TTQS assessment scores, and also further discussed the quality of manufacturing about making a proper developing of the key training items, which decreases money wasting and speed up the efficiency training. According to the experiments, the manufacturers should focuses on the training plan and its purpose, the training monitor and performance must be caution as well. In addition, the proposed paper applied TTQS assessment scores for classification which can precisely achieved a better predicted accuracy, then the enterprises can choose their priority items to modify by their industry characteristics.
Appears in Collections:	[Department of Leisure and Recreation Management] Journal Article

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