A SURVEY ON WASTEWATER TREATMENT (WWT) ANALYSIS USING VARIOUS TECHNIQUES
Abstract
Wastewater is contaminated water that has been affected by human use and also causes environmental pollution. Waste Water Treatment (WWT) is a process of removing contaminants from wastewater and reuses the water in various applications such as Hydroelectric Power Generation, Agriculture, and Radioactivity etc. The developments of various techniques for WWT have been implemented by many researchers. The choice of the suitable treatment techniques is dependent on the wastewater pollutant concentrations such as Biochemical oxygen demand (BOD) and Chemical oxygen demand (COD). This paper explores various techniques like Data Mining, Machine learning, Principal Component Analysis (PCA), Support Vector Machine (SVM), Regression Trees (RT) and provides the estimation of the wastewater quality characteristics.
Keywords
Waste Water Treatment; Data Mining; Machine learning; SVM; PCA; RT;
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PDFDOI: https://doi.org/10.26483/ijarcs.v9i0.5603
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