Bio-communal wastewater treatment plant real-time modeling using an intelligent meta-heuristic approach: A sustainable and green ecosystem

S. I. Abba*, Huseyin Cagan KILINC, Mou Leong Tan, Vahdettin Demir, Iman Ahmadianfar, Bijay Halder, Salim Heddam, Ali H. Jawad, Ahmed M. Al-Areeq, Zaher Mundher Yaseen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Considering the importance of nitrogen and organic carbon in supporting the growth of various algae and organic matters, that improves eutrophication along the water bodies. It is, therefore, essential to develop reliable tools that can help policymakers and experts in-understand the environmental and aquatic importance of these macronutrients in relation to other different hydro-physical and chemical variables. The current research proposes the development of three different data intelligence; Neuro-fuzzy (NF), Support Vector Regression (SVR), and Multivariate Regression (MVR) model integrated with a hybrid Neuro-fuzzy-Shuffled frog-leaping algorithm (NF-SFLA) for the simulation of total Kjeldahl Nitrogen (TKNeff) and total organic carbon (TCODeff) based-organic removal from wastewater treatment plant (WWTP). Both visualized and numerical performance of the single models indicated that NF model combination two (NF-M2) showed superior performance than other models for modeling TKNeff (MAE = 0.0367, NSE = 0.9110) and TCODeff (MAE = 0.0363, NSE = 0.8300). The hybrid NF-SFLA was proposed to improve the performance prediction of both TKNeff and TCODeff from the WWTP effluent. The NF-SFLA-M2 achieves an overwhelming performance improvement of up to 13 % over NF-M2 for TKNeff and TCODeff regarding NSE criteria.

Original languageEnglish
Article number103731
JournalJournal of Water Process Engineering
Volume53
DOIs
StatePublished - Jul 2023

Bibliographical note

Publisher Copyright:
© 2023 Elsevier Ltd

Keywords

  • Artificial intelligence
  • Nitrogen
  • Shuffled frog leaping algorithm
  • Wastewater treatment plant

ASJC Scopus subject areas

  • Biotechnology
  • Safety, Risk, Reliability and Quality
  • Waste Management and Disposal
  • Process Chemistry and Technology

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