1. Gupta, B.,, Rawat, A., Jain, J., Arora, A., Dhami, N. (2017). Analysis of Various Decision Tree Algorithms for Classification in Data Mining. International Journal of Computer Applications, 163(8), 15-19.
2. Ray, P.K., Kishor, N. (2014). Optimal Feature and Decision Tree-Based Classification of Power Quality Disturbances in Distributed Generation Systems. IEEE Transactions on Sustainable on Energy, 5(1), 200-208.
3. Sangita B.P., Deshmukh, S.R. (2011). Use of Support Vector Machine, decision tree and Naive Bayesian techniques for wind speed classification. International Conference on Power and Energy Systems Power and Energy Systems (ICPS).
4. Retscreen Engineering & Cases Textbook, Clean Energy Project Analysis, Clean Energy Decision Support Centre ISBN: 0-662-35670-5 Catalogue no.: M39-97/2003E-PDF, © Minister of Natural Resources Canada 2001-2004. http://unfccc.int/resource/cd_roms/na1/mitigation/Module_5/Module_5_1/b_tools/RETScreen/Manuals/Wind.pdf, last acces date: Feb 27th, 2019.
5. Chien, C. F., Chen, L. F. 2008. Data Mining to Improve Personnel Selection and Enhance Human Capital: A Case Study in High-Technology Industry. Expert Systems with Applications, 34, 280-290.