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A Result Verification of Decision Tree Model for Industrial Wireless Sensors Selection using Analytic Hierarchy Process

机译:基于层次分析法的工业无线传感器选择决策树模型结果验证

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Nowadays, an industrial wireless sensor (IWS) is interested and widely used in a Gas industry in Thailand. There are many vendors trying to improve quality of IWS products for gaining advantage in competitive market. Therefore, choosing the IWS becomes a challenge for users not only the brand name and price but also several factors needed to be considered, e.g., data rate, output power, operating voltage, transmitting current, receiving current, and operating temperature. Selecting the proper IWS is considered as a multi-objective decision problem that is complicated for an engineer and a project manager. The classification method using a Decision Tree)DT(model can be applied to solve such the problem, but the accuracy is depended on the number of historical data. For IWS in the Gas industry in Thailand, not only the number of training and testing data is limited but also there are only a few brands that are chosen regularly. In this paper, the method of applying the DT model for IWS classification and selection is presented. Then, the classification result of the DT model is verified by using an Analytic Hierarchy Process)AHP(for confirming whether it is accurate based on the limit number of historical data. The verification result can be preliminarily ensured that the DT model can be applied as a decision tool for choosing the appropriate IWS accurately.
机译:如今,工业无线传感器(IWS)引起了人们的兴趣,并广泛应用于泰国的天然气行业。有许多供应商试图提高IWS产品的质量,以在竞争激烈的市场中获得优势。因此,选择IWS成为用户的挑战,不仅是品牌名称和价格,而且还需要考虑几个因素,例如,数据速率,输出功率,工作电压,发射电流,接收电流和工作温度。选择合适的IWS被认为是一个多目标决策问题,对于工程师和项目经理来说很复杂。可以采用使用决策树(DT)模型进行分类的方法来解决此类问题,但准确性取决于历史数据的数量,对于泰国天然气行业的IWS,不仅有训练和测试数据的数量,有限,但也很少定期选择品牌,本文提出了将DT模型用于IWS分类和选择的方法,然后使用层次分析法验证DT模型的分类结果流程)AHP(用于基于历史数据的限制数量来确认其是否正确。可以初步确保验证结果,从而可以将DT模型用作决策工具来准确选择合适的IWS。

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