Path Planning Algorithm and ID3 Decision Tree Model Application of Scenic Intelligent Navigation System

Abstract

The assumption space of ID3 algorithm contains all decision trees, and the search space is also a complete assumption space. The current assumptions based on the information gain standard, and uses the information gain to reduce the sensitivity to individual training sample errors. Based on ID3 decision tree algorithm, this paper provides new ideas and methods for the quality optimization of tourist attractions. Firstly, ID3 decision tree algorithm model is constructed based on information entropy theory; Then, based on the literature research and system research methods, the quality evaluation indicator system of tourist attractions is constructed; Finally, based on the mathematical model and evaluation indicator system, the empirical research was carried out, and the data of 17 tourist attractions were collected. The expected research results were obtained according to the data preprocessing, data calculation process, decision tree construction and rule generation process. The research finds that the quality evaluation process of tourist attractions based on ID3 decision tree model, through data preprocessing, data calculation, decision tree construction and decision rules generation, etc. it can be concluded that the "Tourism environment quality" attribute is the most important in this evaluation system, and "Tourism landscape quality" is relatively important. Tourist attractions can improve the work and quality of tourist attractions according to the research results.