Development of an Artificial Intelligence System (AI) Based on Patterns Recognition for the Analysis of Vehicular Routes

Leonardo Luís Röpke, M. Binelo
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Abstract

This work presents the study and development of an Artificial Intelligence system, with focus on K-means algorithms and Artificial Neural Networks, to assist fleet managers in the identification of routes and route deviations. The developed tool has the objective of modernizing the process of identification of routes and deviations of routes. The results show that the Artificial Neural Networks obtained a 100% accuracy rate in the identification of routes, and in the identification of route deviations the RNAs were able to identify 61% of the routes presented. Therefore, RNAs are an excellent technique to be applied to the identification of routes and deviations of routes. The K-means algorithm presented good results when applied in the discovery of similar routes, thus becoming an important tool applied to the work of monitoring vehicles routes.
基于模式识别的车辆路线分析人工智能系统的开发
这项工作介绍了人工智能系统的研究和开发,重点是k均值算法和人工神经网络,以帮助车队管理者识别路线和路线偏差。开发的工具的目标是使路线识别和路线偏差的过程现代化。结果表明,人工神经网络对路线的识别准确率为100%,对路线偏差的识别准确率为61%。因此,rna是一种很好的技术,可以用来识别路线和路线的偏差。K-means算法在相似路线的发现中表现出良好的效果,成为车辆路线监控工作的重要工具。
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