Bi-Objective Optimization through Pareto Frontier Analysis and Artificial Neural Network for Adsorptive Removal of Fluoride by a Novel Al/Olivine Composite-Reference-Cited by-同舟云学术

Bi-Objective Optimization through Pareto Frontier Analysis and Artificial Neural Network for Adsorptive Removal of Fluoride by a Novel Al/Olivine Composite

Published:2018-12 Issue:12 Volume:144 Page:04018126
ISSN:0733-9372
Container-title:Journal of Environmental Engineering
language:en
Short-container-title:J. Environ. Eng.

Author:

Ghosal Partha S.¹,Gupta Ashok K.²

Affiliation:

1. Ph.D. Candidate, Environmental Engineering Division, Dept. of Civil Engineering, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721 302, India.

2. Professor, Environmental Engineering Division, Dept. of Civil Engineering, and, Head, School of Water Resources, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721 302, India (corresponding author).

Publisher

American Society of Civil Engineers (ASCE)

Subject

General Environmental Science,Civil and Structural Engineering,Environmental Chemistry,Environmental Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29EE.1943-7870.0001457

Reference77 articles.

1. Improving response surface methodology by using artificial neural network and simulated annealing

2. Ultrasound-assisted adsorption of Sunset Yellow CFC dye onto Cu doped ZnS nanoparticles loaded on activated carbon using response surface methodology based on central composite design

3. Modeling of Fixed-Bed Column System of Hg(II) Ions on Ostrich Bone Ash/nZVI Composite by Artiﬁcial Neural Network

4. GIS and Artificial Neural Network–Based Water Quality Model for a Stream Network in the Upper Green River Basin, Kentucky, USA

5. Response surface modeling of Carbamazepine (CBZ) removal by Graphene-P25 nanocomposites/UVA process using central composite design

Cited by 10 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Modeling the adsorption process for fluoride removal from groundwater by machine learning;Environmental Progress & Sustainable Energy;2023-07-04

2. A New Model of Environmental-Economic Coordination Prediction Using Credible Neural Network Integration and Big Data Analysis;Security and Communication Networks;2022-11-22

3. Influence of mass-awareness campaign on community behavior pattern changes for safe drinking water availability in a groundwater arsenic-affected area of South Asia;Groundwater for Sustainable Development;2022-08

4. Modeling defluoridation of real-life groundwater by a green adsorbent aluminum/olivine composite: Isotherm, kinetics, thermodynamics and novel framework based on artificial neural network and support vector machine;Journal of Environmental Management;2022-01

5. A multivariate modeling and experimental realization of photocatalytic system of engineered S–C3N4/ZnO hybrid for ciprofloxacin removal: Influencing factors and degradation pathways;Environmental Research;2021-05