An Optimized Way to Deliver Goods by Using Multilayer Artificial Neural Network Model

Abstract

This paper provides way to understand the use of Multi-layer Artificial Neural Network (MANN) Model for getting vehicles flow prediction and finding optimum path to deliver goods based on the vehicles flow data during limited time period. In this manuscript, we design someMulti-layer Artificial NeuralNetwork Model with average speed of vehicles, number of vehicles running on road, time, density of vehicles, day, number of dumb vehicles on the road and many other variables as input variables. We can take some other conditions which are not used in previous studies. Several conditions will not easily predict like behavior of driver, sudden road blockage, rainy seasons, festivals demand and etc. We can observe the least density of vehicles on the road then the vehicle driver selected best predicted way for delivery of the goods. The route of vehicle is decided according to the reliable and high-quality result of Multi-layer Artificial Neural Network Model.