A new approach for wastewater treatment using predictive data mining - A comparative study

Authors

  • P. Pandi Selvi
  • . .

DOI:

https://doi.org/10.14419/ijet.v7i2.32.29784

Keywords:

Predictive Data Mining, Preprocessing, Random Forest, Random Trees, Wastewater Treatment.

Abstract

In the field of science data mining plays a major role in solving complex real world problems. The proposed method uses the predictive approach to determine the quality of water. To carry out the work, waste water samples were collected from textile industries and a dataset was created. Initially, preprocessing of the sample dataset was carried out. Classification is performed with, Random forest and Random Trees. Mean square error and the mean absolute error values were computed and the results are tabulated. Based on this, decision can be made regarding the recycling of the treated water. With the result it is well evident that the proposed method is able to predict the quality in a better way.

 

 

 

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How to Cite

Pandi Selvi, P., & ., . (2018). A new approach for wastewater treatment using predictive data mining - A comparative study. International Journal of Engineering & Technology, 7(2.32), 550–553. https://doi.org/10.14419/ijet.v7i2.32.29784
Received 2019-08-25
Accepted 2019-08-25