Integrating case-based reasoning, knowledge-based approach and Dijkstra algorithm for route finding

Bing Liu, Siew-Hwee Choo, Shee-Ling Lok, Sing-Meng Leong, Soo-Chee Lee, F. Poon, Hwee-Har Tan
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引用次数: 20

Abstract

Imagine you rent a car and plan to drive around an unfamiliar city. Before you go from one place to another, you need to know a good route. In network theory, this is the shortest path problem. Dijkstra's algorithm is often used for solving this problem. However, when the road network of the city is very complicated and dense, which is usually the case, it will take too long for the algorithm to find the shortest path. Furthermore, in reality, things are not as simple as those stated in network theory. For instance, the cost of travel for the same part of the city at different times may not be the same. In this project, we have integrated Dijkstra's algorithm with a knowledge-based approach and case-based reasoning in solving the problem. With this integration, knowledge about the geographical information and past cases are used to help Dijkstra's algorithm in finding a solution. This approach dramatically reduces the computation time required for route finding. A prototype system has been implemented for route finding in Singapore.<>
结合基于案例推理、基于知识的方法和Dijkstra算法进行寻路
想象一下,你租了一辆车,打算在一个不熟悉的城市里开车兜风。在你从一个地方到另一个地方之前,你需要知道一条好的路线。在网络理论中,这是最短路径问题。Dijkstra算法通常用于解决这个问题。然而,当城市的道路网络非常复杂和密集时,通常情况下,算法寻找最短路径的时间会太长。此外,在现实中,事情并不像网络理论中所说的那么简单。例如,在不同的时间去城市的同一地区的旅行费用可能不一样。在这个项目中,我们将Dijkstra算法与基于知识的方法和基于案例的推理相结合来解决问题。通过这种整合,关于地理信息和过去案例的知识被用来帮助Dijkstra算法找到解决方案。这种方法大大减少了寻路所需的计算时间。在新加坡,一个用于寻路的原型系统已经实现。
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