Design and Development of Efficient Cost-Saving Algorithms for Guiding Customer Purchasing Patterns in Modern Consumerism Scenario Using Feed Forward Back Propagation Neural Networks

This research deals with the development of a new architecture. The system deals with self-scanning and self-checkout of the products. Here, we have made an effort to take the system which is a very handy through app. It uses neural networks, fuzzy logic, and genetic algorithms. The database is maintained in the local server, and both mobile and the local host are connected to the same network. As a result, the user can use all the features of this system and send and receive the data which is required by the user. This framework takes care of taxations such as GST. The concept involves designing and implementation of cost-saving algorithms by using feed forward back propagation neural networks for guiding customer purchasing, retrieval, and faster method of accessibility with respect to different patterns. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.