Performance evaluation of artificial intelligence with particle swarm optimization (PSO) to predict treatment water plant DBPs (haloacetic acids).

Journal: Chemosphere
Published Date: Oct 1, 2023

Abstract

The prevention of water-borne diseases requires the disinfection of water consumed. Disinfection by-products, however, are an increasing concern, and they require advanced knowledge of water treatment plants before their release for human consumption. In this study, multivariate non-linear regression (MNR) and adaptive neuro-fuzzy inference system (ANFIS: Grid partition - GP and Sub-clustering - SC) integrated with particle swarm optimization (PSO) were proposed for the prediction of haloacetic acids (HAAs) in actual distribution systems. PSO-ANFIS-GP and PSO-ANFIS-SC were trained and verified for a total of 64 sets of data with eight parameters (pH, Temperature, UVA, DOC, Br; NH-N; NO-N, residual free chlorine). With MNR, R is 0.5184

Authors

  • Anthony I Okoji
    Department of Chemical Engineering, Covenant University, Ota, Ogun state, Nigeria. Electronic address: anthony.okoji@covenantuniversity.edu.ng.
  • Comfort N Okoji
    Department of Biology and Forensic, Admiralty University, Ibusa, Delta state, Nigeria.
  • Olorunfemi S Awarun
    Department of Microbiology, Landmark University, Omu-Aran, Kwara state, Nigeria.

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