Predicting biochemical oxygen demand in wastewater treatment plant using advance extreme learning machine optimized by Bat algorithm.

ABSTRACT: Wastewater quality modelling plays a vital role in planning and management of wastewater treatment plants (WWTP). This paper develops a new hybrid machine learning model based on extreme learning machine (ELM) optimized by Bat algorithm (ELM-Bat) for modelling five day effluent biochemical oxygen demand (BOD₅). Specifically, this hybrid model combines the Bat algorithm for model parameters optimization and the standalone ELM. The proposed model was developed using historical measured effluents wastewater quality variables, i.e., the chemical oxygen demand (COD), temperature, pH, total suspended solid (TSS), specific conductance (SC) and the wastewater flow (Q). The performances of the hybrid ELM-Bat were compared wit

SUBMITTER: Mekaoussi H 

PROVIDER: S-EPMC10637896 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature