Review of Swarm Intelligence for Improving Time Series Forecasting

In many real-world applications, analyzing and predicting the pattern of data in time series plays an important role, ranging from resource allocation in data centers, load schedule in smart grids to energy consumption forecasting, and guiding investor’s decision and trade. This chapter provides a review of some existing swarm intelligence algorithms applied for solving time series forecasting problems by training and optimizing their correspondent models. It also gives a detailed description of the nature and the process of time series forecasting and how models are implemented to predict their future values.