A hybrid method for short-term sensor data forecasting in Internet of Things

In this paper, the hybrid method is proposed for sensor data predicting in the Internet of Things which combining the Ensemble Empirical Mode Decomposition (EEMD), Support Vector Regression (SVR), Particle Swarm Optimization (PSO) algorithm. The proposed hybrid method is examined by several kinds of sensor data. The obtained results confirm the universality, generality and high forecasting accuracy of the hybrid method.