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A rule-based decision support approach for site selection of Automated Teller Machines (ATMs)

机译：基于规则的决策支持方法，用于自动柜员机（ATM）的站点选择

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摘要

The solution of facility site selection problems is of utmost importance for the existence and future of the businesses. When planning for banking services, banks should ensure their accessibility standards by taking their customers and needs into account. For this reason, the accessibility of the services offered via ATM devices is very important. Contrary to the studies that have been widely done in the literature, in this study, the data mining techniques for determining locations of the ATMs, specifically decision tree algorithms were applied to select the best location among candidates considering new ATM installations. In practice, a data set of a private bank’s ATM’s, which in the boundaries of the districts connected to downtown of Kayseri, was used. A decision support model based on rule-based location detection was created from the data set discussed. The correct classification scales were evaluated by applying different algorithms for decision tree method. Among the decision tree algorithms, model estimation accuracy was found to be 92.96% on average. The results were obtained using STATISTICA 10.0 Software.
机译：解决设施选址问题对于企业的生存和未来至关重要。在计划银行服务时，银行应通过考虑客户和需求来确保其可访问性标准。因此，通过ATM设备提供的服务的可访问性非常重要。与文献中广泛进行的研究相反，在这项研究中，使用数据挖掘技术确定ATM的位置，特别是决策树算法，从而在考虑安装新ATM的候选人中选择最佳位置。实际上，使用的是私人银行ATM的数据集，该数据集位于与开塞利市区相连的区域的边界内。从讨论的数据集创建了基于基于规则的位置检测的决策支持模型。通过对决策树方法应用不同的算法来评估正确的分类量表。在决策树算法中，模型估计的准确性平均为92.96％。结果是使用STATISTICA 10.0软件获得的。

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