Intelligent algorithms of construction of public transport routes

Abstract

Today, in public transport planning systems, it is relevant to a search for a possible route with a minimum time. The aim of the work is the development of intelligent algorithms for constructing public transport routes, the development of programs, and the conduct of a computational experiment. Research methods are the theory of neural networks. The paper considers Hopfield neural networks and proposed recurrent neural networks. However, in Hopfield neural networks, the chances of solving this optimization problem decrease as the matrix size increases. A recurrent neural network is proposed, represented by a differential equation to solve this problem. As a result, the number of iterative computations can be reduced by n2 times than in the Hopfield network.