Analysis on the Effect of Intelligentization and Improvement of Tourist Bus Loops Based on Markov Chain Decoupling

Abstract

Based on vehicle positioning and remote data transmission technology, a quantitative analysis method for the impact of intelligent tour bus loops on the choice of transportation means between tourist attractions is developed. Aiming at the problem of undirected graph path planning where the influence of time series is known and the edge weights are known, Markov chains are introduced on the basis of the “0-1-like planning under time series” model, and a Markov chain-based algorithm is established. In this article, we proposed a model for route planning of a tourist bus. When solving, it is assumed that the weight of the edge changes with time, and random variables are introduced, but the past state will not affect the current state, and other conditions remain unchanged. After the constraint model is established, it is simulated by computer and solved using the stochastic gradient descent algorithm. The model makes the tour bus loop intelligent and has good interpretability and robustness.