Traffic Time Series and Deep Learning for an Effective Business Model: Digitalization Process

Abstract

This chapter examines how combining time series study and deep learning can optimize business models using traffic information. It starts by explaining why traffic data is important in today's business settings and lists old ways to analyze it. The chapter continues by exploring how to use deep learning methods like recurrent neural networks (RNNs) and convolutional neural networks (CNNs) to predict and recognize patterns in traffic. Case studies and examples show how useful these methods are in making business operations more efficient, enhancing the customer experience, and helping make better business decisions. It explores upcoming trends and obstacles to using deep learning to help businesses grow.