The book is a summary of a time series forecasting competition that was held a number of years ago. It aims to provide a snapshot of the range of new techniques

Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic

Build predictive models from time-based patterns in your data. Master statistical models including new deep learning approaches for time series forecasting. In

This book presents machine learning and type-2 fuzzy sets for the prediction of time-series with a particular focus on business forecasting applications. It als

Time series data analysis is increasingly important due to the massive production of such data through the internet of things, the digitalization of healthcare,