Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Artificial Intelligence-Assisted Prediction of Effluent Phosphorus in a Full-Scale Wastewater Treatment Plant with Missing Phosphorus Input and Removal Data
Yanran Xu, Zixuan Wang, Shaker Nairat, et al.
ACS ES&T Water (2023) Vol. 4, Iss. 3, pp. 880-889
Closed Access | Times Cited: 27

Showing 1-25 of 27 citing articles:

Livestock and poultry farm wastewater treatment and its valorization for generating value-added products: Recent updates and way forward
Sakshi Vaishnav, Tapendra Saini, Anuj Chauhan, et al.
Bioresource Technology (2023) Vol. 382, pp. 129170-129170
Closed Access | Times Cited: 41
Enhancing wastewater treatment efficiency through machine learning-driven effluent quality prediction: A plant-level analysis
Maria Alice Prado Cechinel, Juliana Neves, João Vitor Rios Fuck, et al.
Journal of Water Process Engineering (2024) Vol. 58, pp. 104758-104758
Closed Access | Times Cited: 15
Enhancing phosphorus source apportionment in watersheds through species-specific analysis
Yuansi Hu, Mengli Chen, Jia Pu, et al.
Water Research (2024) Vol. 253, pp. 121262-121262
Closed Access | Times Cited: 15
Advancements in Biochar Modification for Enhanced Phosphorus Utilization in Agriculture
Nazir Ahmed, Lifang Deng, Chuan Wang, et al.
Land (2024) Vol. 13, Iss. 5, pp. 644-644
Open Access | Times Cited: 12
Deep learning based simulators for the phosphorus removal process control in wastewater treatment via deep reinforcement learning algorithms
Esmaeel Mohammadi, Mikkel Stokholm-Bjerregaard, Aviaja Anna Hansen, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 107992-107992
Open Access | Times Cited: 8
Enhancing wastewater treatment through artificial intelligence: A comprehensive study on nutrient removal and effluent quality prediction
Offir Inbar, Dror Avisar
Journal of Water Process Engineering (2024) Vol. 61, pp. 105212-105212
Closed Access | Times Cited: 8
An integrated feature selection and hyperparameter optimization algorithm for balanced machine learning models predicting N2O emissions from wastewater treatment plants
Mostafa Khalil, Ahmed AlSayed, Yang Liu, et al.
Journal of Water Process Engineering (2024) Vol. 63, pp. 105512-105512
Open Access | Times Cited: 8
Insights into the application of explainable artificial intelligence for biological wastewater treatment plants: Updates and perspectives
Abdul Gaffar Sheik, Arvind Kumar, Chandra Sainadh Srungavarapu, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 144, pp. 110132-110132
Open Access | Times Cited: 1
Adaptive prediction for effluent quality of wastewater treatment plant: Improvement with a dual-stage attention-based LSTM network
Tong An, Kuanliang Feng, Peijin Cheng, et al.
Journal of Environmental Management (2024) Vol. 359, pp. 120887-120887
Closed Access | Times Cited: 6
Applications of artificial intelligence technologies in water environments: From basic techniques to novel tiny machine learning systems
Majid Bagheri, Nakisa Farshforoush, Karim Bagheri, et al.
Process Safety and Environmental Protection (2023) Vol. 180, pp. 10-22
Open Access | Times Cited: 14
Ternary deep eutectic solvents: Evaluations based on how their physical properties affect energy consumption during post-combustion CO2 capture
Jiasi Sun, Yuki Sato, Yuka Sakai, et al.
Energy (2023) Vol. 270, pp. 126901-126901
Closed Access | Times Cited: 13
Management strategy of granular sludge settleability in saline denitrification: Insights from machine learning
Junbeom Jeon, Minkyu Choi, Suin Park, et al.
Chemical Engineering Journal (2024) Vol. 493, pp. 152747-152747
Closed Access | Times Cited: 4
Data-driven models for phosphorus forecasting in wastewater treatment plants: A tool to enhance operation
Florencia Caro, Claudia Santiviago, Jimena Ferreira, et al.
Journal of environmental chemical engineering (2025), pp. 116259-116259
Closed Access
Prediction of biogas production in anaerobic digestion of a full‐scale wastewater treatment plant using ensembled machine learning models
Jiasi Sun, Yanran Xu, Shaker Nairat, et al.
Water Environment Research (2023) Vol. 95, Iss. 6
Closed Access | Times Cited: 10
Machine learning facilitated the conceptual design of an alum dosing system for phosphorus removal in a wastewater treatment plant
Jiasi Sun, Yanran Xu, Haoran Yang, et al.
Chemosphere (2024) Vol. 351, pp. 141154-141154
Open Access | Times Cited: 2
Nature-Based Solutions and Climate Resilience: A Bibliographic Perspective through Science Mapping Analysis
Farnoosh Vazin, Daniel W.M. Chan, Toktam Hanaee, et al.
Buildings (2024) Vol. 14, Iss. 6, pp. 1492-1492
Open Access | Times Cited: 1
Predicting the Occurrence of Substituted and Unsubstituted, Polycyclic Aromatic Compounds in Coking Wastewater Treatment Plant Effluent using Machine Learning Regression
Rohit Pal, Luke Arcamo, Ramin Farnood
Chemosphere (2024) Vol. 361, pp. 142476-142476
Closed Access | Times Cited: 1
Pipe Failure Prediction in the Water Distribution System Using a Deep Graph Convolutional Network and Temporal Failure Series
Yanran Xu, Zhen He
ACS ES&T Engineering (2024) Vol. 4, Iss. 9, pp. 2252-2262
Closed Access | Times Cited: 1
Understanding machine learning predictions of wastewater treatment plant sludge with explainable artificial intelligence
Fuad Bin Nasir, Jin Li
Water Environment Research (2024) Vol. 96, Iss. 10
Closed Access | Times Cited: 1
Machine learning assisted prediction and process validation of electrochemically induced phosphorus recovery from wastewater
Alisha Zaffar, Muhil Raj Prabhakar, Chong Liu, et al.
Journal of environmental chemical engineering (2024), pp. 114271-114271
Closed Access | Times Cited: 1
New Perspective for the Prediction of Pollutant Removal Efficiency in Constructed Wetlands: Using a Genetic Algorithm-Assisted Machine Learning Model
Shu-Zhe Zhang, Hong Jiang
ACS ES&T Water (2024) Vol. 4, Iss. 11, pp. 5053-5064
Closed Access | Times Cited: 1
Comparative Analysis of Machine Learning Models and Explainable Artificial Intelligence for Predicting Wastewater Treatment Plant Variables
Fuad Bin Nasir, Jin Li
Advances in Environmental and Engineering Research (2024) Vol. 05, Iss. 04, pp. 1-23
Open Access
Applications of Artificial Intelligence, Machine Learning, and Data Analytics in Water Environments
Huichun Zhang, Carla A. Ng
ACS ES&T Water (2024) Vol. 4, Iss. 3, pp. 761-763
Open Access
Advancing Sustainable Water Quality Monitoring and Remediation in Malaysia: Innovative Analytical Solutions for Detecting and Removing Emerging Contaminants
May Lee Low, Jamilah Karim, Nurfaizah Abu Tahrim, et al.
ACS ES&T Water (2024) Vol. 4, Iss. 11, pp. 4758-4773
Closed Access
Machine Learning for Monitoring Per- and Polyfluoroalkyl Substance (Pfas) in California's Wastewater Treatment Plants: An Assessment of Occurrence and Fate
Jialin Dong, Seungjun Kim, S. Young, et al.
(2024)
Closed Access
Page 1 - Next Page

Scroll to top