Optimisation and interpretation of machine and deep learning models for improved water quality management in Lake Loktak-Reference-Cited by-同舟云学术

Optimisation and interpretation of machine and deep learning models for improved water quality management in Lake Loktak

Published:2024-02 Issue: Volume:351 Page:119866
ISSN:0301-4797
Container-title:Journal of Environmental Management
language:en
Short-container-title:Journal of Environmental Management

Author:

Talukdar Swapan,Shahfahad ^ORCID,Bera Somnath,Naikoo Mohd Waseem,Ramana G V,Mallik Santanu,Kumar Potsangbam Albino,Rahman Atiqur^ORCID

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Waste Management and Disposal,General Medicine,Environmental Engineering

Reference86 articles.

1. Modeling the infiltration rate of wastewater infiltration basins considering water quality parameters using different artificial neural network techniques;Abdalrahman;Eng. Appl. Comput. Fluid Mech.,2022

2. Application of adaptive neuro-fuzzy inference system (ANFIS) to estimate the biochemical oxygen demand (BOD) of Surma River;Ahmed;J. King Saud Univ.-Eng. Sci.,2017

3. Various natural and anthropogenic factors responsible for water quality degradation: a review;Akhtar;Water,2021

4. Hydrogeochemical assessment and evaluation of groundwater quality in selected areas of Bishnupur district, Manipur;Alam;J. Geol. Soc. India,2020

5. Coupling machine and deep learning with explainable artificial intelligence for improving prediction of groundwater quality and decision-making in arid region, Saudi arabia;Alshehri;Water,2023

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