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OpenAlex Citation Counts

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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:

Predicting compressive strength of manufactured-sand concrete using conventional and metaheuristic-tuned artificial neural network
Yinghao Zhao, Hesong Hu, Chaolin Song, et al.
Measurement (2022) Vol. 194, pp. 110993-110993
Closed Access | Times Cited: 90

Showing 1-25 of 90 citing articles:

Application of Meta-Heuristic Algorithms for Training Neural Networks and Deep Learning Architectures: A Comprehensive Review
Mehrdad Kaveh, Mohammad Saadi Mesgari
Neural Processing Letters (2022) Vol. 55, Iss. 4, pp. 4519-4622
Open Access | Times Cited: 129
The effect of carbon dioxide emissions on the building energy efficiency
Ji Min, Gongxing Yan, Azher M. Abed, et al.
Fuel (2022) Vol. 326, pp. 124842-124842
Closed Access | Times Cited: 92
Autonomous surface crack identification of concrete structures based on an improved one-stage object detection algorithm
Pei‐Rong Wu, Airong Liu, Jiyang Fu, et al.
Engineering Structures (2022) Vol. 272, pp. 114962-114962
Closed Access | Times Cited: 73
Prediction and optimization model of sustainable concrete properties using machine learning, deep learning and swarm intelligence: A review
Shiqi Wang, Peng Xia, Keyu Chen, et al.
Journal of Building Engineering (2023) Vol. 80, pp. 108065-108065
Closed Access | Times Cited: 61
A novel swarm intelligence: cuckoo optimization algorithm (COA) and SailFish optimizer (SFO) in landslide susceptibility assessment
Rana Muhammad Adnan Ikram, Atefeh Ahmadi Dehrashid, Binqiao Zhang, et al.
Stochastic Environmental Research and Risk Assessment (2023) Vol. 37, Iss. 5, pp. 1717-1743
Closed Access | Times Cited: 44
Isotherms, kinetics and thermodynamic mechanism of methylene blue dye adsorption on synthesized activated carbon
Atef El Jery, Heba Saed Kariem Alawamleh, Mustafa Humam Sami, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 34
A Comparative Analysis of Machine Learning Models in Prediction of Mortar Compressive Strength
R. Gayathri, Shola Usharani, Lenka Čepová, et al.
Processes (2022) Vol. 10, Iss. 7, pp. 1387-1387
Open Access | Times Cited: 43
LGBM-based modeling scenarios to compressive strength of recycled aggregate concrete with SHAP analysis
Bin Xi, Enming Li, Yewuhalashet Fissha, et al.
Mechanics of Advanced Materials and Structures (2023) Vol. 31, Iss. 23, pp. 5999-6014
Closed Access | Times Cited: 29
Hydrological drought forecasting and monitoring system development using artificial neural network (ANN) in Ethiopia
Kassa Abera Tareke, Admasu Gebeyehu Awoke
Heliyon (2023) Vol. 9, Iss. 2, pp. e13287-e13287
Open Access | Times Cited: 28
Multilayer Perceptron and Their Comparison with Two Nature-Inspired Hybrid Techniques of Biogeography-Based Optimization (BBO) and Backtracking Search Algorithm (BSA) for Assessment of Landslide Susceptibility
Hossein Moayedi, Peren Jerfi Canatalay, Atefeh Ahmadi Dehrashid, et al.
Land (2023) Vol. 12, Iss. 1, pp. 242-242
Open Access | Times Cited: 23
Predictive models in machine learning for strength and life cycle assessment of concrete structures
A. Dinesh, B. Rahul Prasad
Automation in Construction (2024) Vol. 162, pp. 105412-105412
Closed Access | Times Cited: 15
An ultrafast and robust structural damage identification framework enabled by an optimized extreme learning machine
Xinwei Wang, Yinghao Zhao, Zhihao Wang, et al.
Mechanical Systems and Signal Processing (2024) Vol. 216, pp. 111509-111509
Closed Access | Times Cited: 9
Predicting compressive strength of concrete using advanced machine learning techniques: a combined dataset approach
Abinash Mandal
Asian Journal of Civil Engineering (2025)
Open Access | Times Cited: 1
Artificial intelligence techniques in advanced concrete technology: A comprehensive survey on 10 years research trend
Ramin Kazemi
Engineering Reports (2023) Vol. 5, Iss. 9
Open Access | Times Cited: 21
Hybrid BO-XGBoost and BO-RF Models for the Strength Prediction of Self-Compacting Mortars with Parametric Analysis
Asif Ahmed, Wei Song, Yumeng Zhang, et al.
Materials (2023) Vol. 16, Iss. 12, pp. 4366-4366
Open Access | Times Cited: 21
A novel hybrid Harris hawk optimization and sine cosine algorithm based home energy management system for residential buildings
Kaushik Paul, Debolina Hati
Building Services Engineering Research and Technology (2023) Vol. 44, Iss. 4, pp. 459-480
Closed Access | Times Cited: 20
Evaluation of waste management and energy saving for sustainable green building through analytic hierarchy process and artificial neural network model
Yanjie Lu, Yisu Ge, Guodao Zhang, et al.
Chemosphere (2023) Vol. 318, pp. 137708-137708
Closed Access | Times Cited: 18
Compressive Strength Prediction of Rice Husk Ash Concrete Using a Hybrid Artificial Neural Network Model
Chuanqi Li, Xiancheng Mei, Daniel Dias, et al.
Materials (2023) Vol. 16, Iss. 8, pp. 3135-3135
Open Access | Times Cited: 17
A systematic literature review of AI-based prediction methods for self-compacting, geopolymer, and other eco-friendly concrete types: Advancing sustainable concrete
Tariq Ali, Mohamed Hechmi El Ouni, Muhammad Zeeshan Qureshi, et al.
Construction and Building Materials (2024) Vol. 440, pp. 137370-137370
Closed Access | Times Cited: 8
Utilizing machine learning approaches within concrete technology offers an intelligent perspective towards sustainability in the construction industry: a comprehensive review
Suhaib Rasool Wani, Manju Suthar
Multiscale and Multidisciplinary Modeling Experiments and Design (2024) Vol. 8, Iss. 1
Closed Access | Times Cited: 6
Bayesian updating with adaptive, uncertainty-informed subset simulations: High-fidelity updating with multiple observations
Zeyu Wang, Abdollah Shafieezadeh
Reliability Engineering & System Safety (2022) Vol. 230, pp. 108901-108901
Open Access | Times Cited: 27
A Study of Optimization in Deep Neural Networks for Regression
Chieh-Huang Chen, Jung-Pin Lai, Yu-Ming Chang, et al.
Electronics (2023) Vol. 12, Iss. 14, pp. 3071-3071
Open Access | Times Cited: 16
Prediction Models for Estimating Compressive Strength of Concrete Made of Manufactured Sand Using Gene Expression Programming Model
Kaffayatullah Khan, Babatunde Abiodun Salami, Arshad Jamal, et al.
Materials (2022) Vol. 15, Iss. 17, pp. 5823-5823
Open Access | Times Cited: 20
Enhanced artificial intelligence for electrochemical sensors in monitoring and removing of azo dyes and food colorant substances
Yujia Wu, Arwa Abdulkreem AL‐Huqail, Zainab A. Farhan, et al.
Food and Chemical Toxicology (2022) Vol. 169, pp. 113398-113398
Closed Access | Times Cited: 19
Vulnerability assessment of road networks to landslide hazards in a dry-mountainous region
Saleh Yousefi, Abolfazl Jaafari, Aleksandar Valjarević, et al.
Environmental Earth Sciences (2022) Vol. 81, Iss. 22
Closed Access | Times Cited: 19
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