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PROVIDING A WEB-BASED PLATFORM BASED ON PREDICTED WEIGHTS FROM EXISTING CONDITIONS

机译:基于来自现有条件的预测权重提供基于Web的平台

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Nowadays traffic problem has become a major dilemma due to the expansion of urbanization and the development of transportation. Traffic itself is the result of various factors, which can have an impact on the environment, and it has also destructive effects on human living. Finding a suitable method to reduce the negative effect of traffic has always been the subject of research in this area. Accordingly, there are different algorithms management and administrative procedures for solving this problem.In this research, a web-based platform is designed using artificial intelligence algorithms, which predicts traffic information in different intervals along with online collecting traffic data. This feature allows the user to instantly view future information of urban traffic. On the other hand, in the proposed model, the transport network edges are determined based on traffic prediction algorithms, which makes route finding closer to reality.The model is implemented on the 7th and 8th districts of Tehran. The algorithm has been applied to more than 100 cases and the results have been compared with existing algorithms. The results of this comparison show that in addition to higher precision, the proposed platform is averagely 10 minutes faster than similar programs.
机译:如今,由于城市化扩大和交通的发展,现在交通问题已成为一个重大的困境。交通本身是各种因素的结果,这可能对环境产生影响,并且对人类生活也有破坏性影响。寻找合适的方法来降低交通的负面影响一直是该领域研究的主题。因此,存在不同的算法管理和管理程序,用于解决这一问题。在本研究中,使用人工智能算法设计了一种基于Web的平台,其以不同的间隔预测交通信息以及在线收集业务数据。此功能允许用户立即查看城市交通的未来信息。另一方面,在所提出的模型中,传输网络边缘基于流量预测算法确定,这使得路线发现更接近现实。模型是在德黑兰的第7和第8区实现的。该算法已应用于超过100例,并将结果与​​现有算法进行了比较。该比较的结果表明,除了更高的精度之外,所提出的平台比类似的程序快10分钟。

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