Machine Learning-Based Sine-Cosine Algorithm for Wastewater Quality Assessment Using Activated Carbon

Activated carbon is one of the most highly proven adsorbents for organic chemicals from wastewater. It acts as a filter and adsorbs various has large pore size strong adsorptive capacity. The quality wastewater generally determined by chemical oxygen demand (COD), biochemical (BOD5), total suspended solids (TSSs), phosphorus (TP), nitrogen (TN). Wastewater contaminant measurement significant saving aquatic life reusing treated water. Adsorption contaminants that contribute indicators uses machine learning algorithm prediction. Many research works have been done, issues are inefficiency time consuming in adsorption activated management. To overcome these issues, this paper introduces hybrid technique Voting-Based Extreme Learning Machine with sine cosine (VELM-SCA). accuracy VELM-SCA classification water status produced improved 0.97.