C4.5 Decision Tree Machine Learning Algorithm Based GIS Route Identification
C4.5 Decision Tree Machine Learning Algorithm Based GIS Route Identification
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DOI：
10.1109/icufn.2018.8436994
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发表时间：
2018-07
期刊：
影响因子：
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通讯作者：
P. K. Dalela;P. Bansal;Arun Yadav;S. Majumdar;Anurag Yadav;V. Tyagi
中科院分区：
文献类型：
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作者：
P. K. Dalela;P. Bansal;Arun Yadav;S. Majumdar;Anurag Yadav;V. Tyagi
地理信息系统（GIS）技术和人工智能（AI）的进步支持决策支持系统（DSS）和空间决策支持系统（SDSS）的发展，以解决复杂的现实生活问题。其实施领域涵盖从国防到民政部门、从气象到灾害管理、从交通分析到网络规划等各个领域。远程信息处理发展中心（CDOT）开发了一个软件系统，用于分析和识别铺设光纤的最佳GIS路线，该系统的规划由巴拉特宽带网络有限公司（BBNL）完成。 BBNL 已完成将客户驻地设备 (CPE) 连接到中心局 (CO) 的规划。这些路线是通过人工足部勘测来规划的。该软件系统分析规划的GIS路线是否最优，并提出优化的光纤路线规划建议。在本文中，我们针对上述项目执行过程中遇到的问题提出了解决方案。我们提出了基于 C4.5 决策树机器学习算法的算法解决方案。该软件系统首先根据用户输入进行学习，然后创建规则。使用这些规则软件系统可以通过 GIS 提供光网络的光纤规划。该算法使用机器学习，从使用不同 GIS 数据源计算的一组路线中找到最佳可能路线。
Advancement of Geographic Information System (GIS) technologies and Artificial Intelligence (AI) supports development of Decision Support System (DSS) and Spatial Decision Support System (SDSS) to solve complex real life problems. Its areas of implementation encompasses diverse fields from defense to civil departments, from meteorology to disaster management, from traffic analysis to network planning etc. Centre for Development of Telematics (CDOT) has developed a software system for analyzing and identifying optimized GIS routes for laying optical fiber who's planning has been done by Bharat Broadband Network Limited (BBNL). BBNL has done planning for connecting Customer Premise Equipment (CPE) to the Central Office (CO). These routes have been planned by doing manual foot survey. This software system analyses whether the planned GIS routes are optimal or not and suggests optimized fiber routes for planning. In this paper we have presented a solution to the problem that we faced during above mentioned project execution. We have suggested an algorithmic solution based on C4.5 Decision Tree Machine Learning Algorithm. This software system first learns based on user input and then creates rules. Using these rules software system provides fiber planning of optical network over GIS. This algorithm, using machine learning, finds best possible route from a set of routes calculated using different GIS data sources.