Synergistic Approach for Combining SVM Algorithms for Wind Speed Prediction

Authors: Wani, M.A. and Farooq, H.

Journal: 7th International IEEE Conference on Renewable Energy Research and Applications, ICRERA 2018

Pages: 1450-1455

ISBN: 9781538659823

DOI: 10.1109/ICRERA.2018.8566789

Abstract:

This work presents synergistic approach for combining Directed Acyclic Graph (DAG), Binary Tree (BT) and Binary Decision Tree (BDT) based Support Vector Machine (SVM) algorithms for predicting wind speed. The proposed approach and individual algorithms are evaluated on wind speed data that has many samples divided into training and test data sets. The proposed approach of using the synergistic approach produces better results than Directed Acyclic Graph, Binary Tree, and Binary Decision Tree (BDT) based multiclass SVM algorithms individually.

Source: Scopus