一种基于累积接近度评价的智能寻路方法

Yang Yaw Chang, S. Yung, R. Chiong
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引用次数: 1

摘要

今天,日益增加的交通和复杂的现代道路网络使得找到一条从一个地方到另一个地方的好路线成为一项不平凡的任务。人们提出了许多搜索算法来解决这个问题,其中最著名的是Dijkstra算法、Johnson算法和A*算法。虽然这些算法在寻径方面是有效的,但它们在计算方面是浪费的。在本文中,我们提出了一项研究,以检查基于婆罗洲岛一些主要城市和城镇的无知搜索和启发式搜索。我们提出了一种新的智能寻路算法,使用更好的评价标准和累积接近评分的概念。结果表明,该方法不仅减少了计算所需的时间和空间,而且在寻径精度和寻径短度方面取得了较好的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Novel Approach for Intelligent Route Finding through Cumulative Proximity Evaluation
Today, the increased traffic and complex modern road network have made finding a good route from one location to another a non-trivial task. Many search algorithms have been proposed to solve the problem, and the most well-known being Dijkstra's algorithm, Johnson's algorithm and A*. While these algorithms are effective for path finding, they are wasteful in terms of computation. In this paper, we present a study to examine both uninformed search and heuristic search based on some major cities and towns in Borneo Island. We propose a novel algorithm for intelligent route finding using better evaluation criteria and the notion of cumulative proximity score. We show that this proposed technique is able to reduce the time and space required in computation, and also produce better result in terms of a.ccuracy and shortness of path found.
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