References

  1. S. Dilmi, M. Ladjal, A novel approach for water quality classification based on the integration of deep learning and feature extraction techniques, Chemom. Intell. Lab. Syst., 214 (2021) 104329, doi: 10.1016/j.chemolab.2021.104329.
  2. S.M. Saghebian, M.T. Sattari, R. Mirabbasi, M. Pal, Ground water quality classification by decision tree method in Ardebil region, Iran, Arabian J. Geosci., 7 (2014) 4767–4777.
  3. K. Sulaiman, L.H. Ismail, M.A.M. Razi, M.S. Adnan, R. Ghazali, Water quality classification using an artificial neural network (ANN), IOP Conf. Ser.: Mater. Sci. Eng., 601 (2019) 012005,
    doi: 10.1088/1757-899X/601/1/012005.
  4. U. Shafi, R. Mumtaz, H. Anwar, A.M. Qamar, H. Khurshid, Surface Water Pollution Detection Using Internet of Things, 2018 15th International Conference on Smart Cities: Improving Quality of Life Using ICT & IoT (HONET-ICT), Islamabad, Pakistan, 2018.
  5. D. Dezfooli, S.-M. Hosseini-Moghari, K. Ebrahimi, S. Araghinejad, Classification of water quality status based on minimum quality parameters: application of machine learning techniques, Model. Earth Syst. Environ., 4 (2018) 311–324.
  6. R. Prakash, V.P. Tharun, S.R. Devi, A Comparative Study of Various Classification Techniques to Determine Water Quality, Proceedings of the 2nd International Conference on Inventive Communication and Computational Technologies (ICICCT 2018), Coimbatore, India, 2018.
  7. N.H. Abdul Malek, W.F. Wan Yaacob, S.A. Md Nasir, N. Shaadan, Prediction of water quality classification of the Kelantan River Basin, Malaysia, using machine learning techniques, Water, 14 (2022) 1067, doi: 10.3390/w14071067.
  8. J.P. Nair, M.S. Vijaya, River water quality prediction and index classification using machine learning, J. Phys.: Conf. Ser., 2325 (2022) 012011, doi: 10.1088/1742-6596/2325/1/012011.
  9. A. Kaur, M. Khurana, P. Kaur, M. Kaur, Classification and Analysis of Water Quality Using Machine Learning Algorithms, S.K. Sabut, A.K. Ray, B. Pati, U.R. Acharya, Eds., Proceedings of International Conference on Communication, Circuits, and Systems. Lecture Notes in Electrical Engineering, Springer, Singapore 2021,
    pp. 389–398.
  10. L.J. Cao, K.S. Chua, W.K. Chong, H.P. Lee, Q.M. Gu, A comparison of PCA, KPCA and ICA for dimensionality reduction in support vector machine, Neurocomputing, 55 (2003) 321–336.
  11. A. Widodo, B.-S. Yang, Application of nonlinear feature extraction and support vector machines for fault diagnosis of induction motors, Expert Syst. Appl., 33 (2007) 241–250.
  12. B. Scholkopf, A. Smola, K.R. Muller, Nonlinear component analysis as a Kernel eigenvalue problem, Neural Comput., 10 (1998) 1299–1319.