Machine learning framework for oxytetracycline removal using nanostructured cupric oxide supported on magnetic chitosan alginate biocomposite.

ABSTRACT: This research proposes a machine learning controlled method for removing the antibiotic oxytetracycline (OTC) from liquids through the use of nanostructured cupric oxide (CuO) nanoparticles. These nanoparticles are attached to magnetic chitosan/alginate biocomposites (CuO-M-CAB). The dataset consisted of 42 experimentally generated samples, systematically created using key parameters (X1: antibiotic concentration, X2: pH, X3: reaction time, and X4: adsorbent concentration). Prior to applying machine learning models, preprocessing steps were performed, including normalization using Min-Max Scaling to confine all features within the [0,1] range, outlier detection and removal of anomalous values, correlation analysis to avoid redundancy and multicollinearity, and data splitting into training

SUBMITTER: Rasoulzadeh H 

PROVIDER: S-EPMC12274579 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature