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首页> 外文期刊>International Journal of Signal and Imaging Systems Engineering >Artificial-intelligence-based heuristic searching tools and knowledge representation to solve cryptography problems, puzzles, vehicle detection and path finding
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Artificial-intelligence-based heuristic searching tools and knowledge representation to solve cryptography problems, puzzles, vehicle detection and path finding

机译:基于人工智能的启发式搜索工具和知识表示,解决加密问题,谜题,车辆检测和路径发现

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摘要

The objective of this paper is to present different artificial-intelligence-based heuristic searching algorithms, such as the ones in this paper: the breadth-first search (BFS), depth-first search (DFS), Best-First Search, and A~* and AO~* searching techniques. The BFS and DFS help solve puzzles and simple Caesar cipher substitution problems. In this paper, plain text is obtained from the given cipher text using the BFS and DFS. The A~* approach is used to solve puzzles and find the best path between a start city and a destination city. Finally, the AO~* algorithm graph is drawn to find a vehicle in heavy traffic in cities. It is justified that the artificial intelligence tools discussed in this paper are successfully used to solve cryptographic problems, puzzles, path finding and vehicle detection.
机译:本文的目的是呈现不同的人工智能基于启发式搜索算法,例如本文中的诸如此类:宽度第一搜索(BFS),深度第一搜索(DFS),最佳首先搜索和A. 〜*和ao〜*搜索技术。 BFS和DFS有助于解决难题和简单的凯撒密密码替代问题。 在本文中,使用BFS和DFS从给定的密码文本获得纯文本。 A〜*方法用于解决难题并找到一个开始城市和目的地城市之间的最佳路径。 最后,绘制了AO〜*算法图,以找到城市繁忙交通的车辆。 本文讨论的人工智能工具是合理的,以解决加密问题,谜题,路径发现和车辆检测。

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