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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:

Compressive strength of concrete material using machine learning techniques
Satish Paudel, Anil Pudasaini, Rajesh Kumar Shrestha, et al.
Cleaner Engineering and Technology (2023) Vol. 15, pp. 100661-100661
Open Access | Times Cited: 51

Showing 26-50 of 51 citing articles:

Evaluating and strengthening low-rise reinforced concrete buildings constructed in Nepal
Bikram Bhusal, Anuj Pradhananga, Satish Paudel, et al.
Structures (2024) Vol. 63, pp. 106388-106388
Closed Access | Times Cited: 3
Machine learning assisted prediction of the mechanical properties of carbon nanotube‐incorporated concrete
Muhammad Imran, Hassan Amjad, Shayan Ali Khan, et al.
Structural Concrete (2024)
Closed Access | Times Cited: 3
Machine learning based prediction of compressive and flexural strength of recycled plastic waste aggregate concrete
Yılmaz Yılmaz, Safa Nayır
Structures (2024) Vol. 69, pp. 107363-107363
Closed Access | Times Cited: 3
Machine learning (ML) algorithms for seismic vulnerability assessment of school buildings in high-intensity seismic zones
Muhammad Zain, Ulrike Dackermann, Lapyote Prasittisopin
Structures (2024) Vol. 70, pp. 107639-107639
Closed Access | Times Cited: 3
Data-driven strategy for evaluating the response of eco-friendly concrete at elevated temperatures for fire resistance construction
Fahad Alsharari, Bawar Iftikhar, Md. Alhaz Uddin, et al.
Results in Engineering (2023) Vol. 20, pp. 101595-101595
Open Access | Times Cited: 7
Effect of sulfate freeze-thaw on the stress-strain relationship of recycled coarse aggregate self-compacting concrete: Experimental and machine learning algorithms
Chuanlei Zheng, Yijiang Liu, Luoyin Li, et al.
Construction and Building Materials (2024) Vol. 449, pp. 138383-138383
Closed Access | Times Cited: 2
Seismic performance evaluation and strengthening of RC beam-column joints adopted in Nepal
Bikram Bhusal, Satish Paudel, Ganchai Tanapornraweekit, et al.
Structures (2023) Vol. 57, pp. 105205-105205
Closed Access | Times Cited: 6
Predictive analysis of concrete slump using a stochastic search-consolidated neural network
Yunwen Zhou, Zhihai Jiang, Xizhen Zhu
Heliyon (2024) Vol. 10, Iss. 10, pp. e30677-e30677
Open Access | Times Cited: 1
A Comparative Analysis of Traditional and Machine Learning Methods in Forecasting the Stock Markets of China and the US
Shangshang Jin
International Journal of Advanced Computer Science and Applications (2024) Vol. 15, Iss. 4
Open Access | Times Cited: 1
Performance Comparison of Artificial Neural Network and Random Forest Models for Predicting the Compressive Strength of Fibre-Reinforced GGBS-Based Geopolymer Concrete Composites
Shimol Philip, M. Nidhi
Materials Circular Economy (2024) Vol. 6, Iss. 1
Closed Access | Times Cited: 1
Prediction of central deflection and slenderness limit for lateral stability of simply supported concrete beam using machine learning techniques
Rashid Mustafa, Md Talib Ahmad, Akash Kumar, et al.
Asian Journal of Civil Engineering (2024) Vol. 25, Iss. 7, pp. 5443-5466
Closed Access | Times Cited: 1
Advancing Civil Engineering with AI and Machine Learning: From Structural Health to Sustainable Development
Dimitrios Sargiotis
(2024)
Closed Access | Times Cited: 1
Prediction of autogenous shrinkage in ultra-high-performance concrete (UHPC) using hybridized machine learning
Md Muzammal Hoque, Ajad Shrestha, Sanjog Chhetri Sapkota, et al.
Asian Journal of Civil Engineering (2024)
Closed Access | Times Cited: 1
Optimized Hybrid XGBoost-CatBoost Model for Enhanced Prediction of Concrete Strength and Reliability Analysis Using Monte Carlo Simulations
Tuan Nguyen‐Sy
Applied Soft Computing (2024), pp. 112490-112490
Closed Access | Times Cited: 1
Utilizing Data-Driven Methods to Predict the Fatigue Life of Cement Concrete Considering Corrosive Environmental Factors
Prof. K.R. Kashyzadeh
Deleted Journal (2023) Vol. 1, Iss. 3
Open Access | Times Cited: 2
Forecasting the Properties of Concrete Employing Experimental Data Using Machine Learning Algorithms
Abhay K. Jha, R.S. Parihar, Navneet Dongre, et al.
European Journal of Theoretical and Applied Sciences (2024) Vol. 2, Iss. 3, pp. 259-266
Open Access
Deep Learning Projections for High-Performance Concrete Strength Forecasting
Rupesh Kumar Tipu, Owais Ahmad Shah, Satvik Vats, et al.
(2024), pp. 1-4
Closed Access
Comparing the Properties of Concrete (Experimental Data) Using Machine Learning Algorithms
Abhay K. Jha, R.S. Parihar, Navneet Dongre, et al.
Deleted Journal (2024) Vol. 2, Iss. 3, pp. 186-193
Open Access
Machine learning prediction and optimization of compressive strength for blended concrete by applying ANN and genetic algorithm
G. Satyanarayana, C. Vivek Kumar, R. M. Karthikeyan, et al.
Cogent Engineering (2024) Vol. 11, Iss. 1
Open Access
Experimental and Simulation Study on the Stress Characteristics of Precast U-Shaped Beam Slab of Prestressed Concrete for High-Speed Railways
Binghe Zhang, Yicai Yang, Haijun Jiang, et al.
Lecture notes in civil engineering (2024), pp. 110-116
Closed Access
Predictive modeling of compressive strength of geopolymer concrete before and after high temperature applying machine learning algorithms
Haifeng Yang, Hongrui Li, Jiasheng Jiang
Structural Concrete (2024)
Closed Access
Comparing durability and compressive strength predictions of hyperoptimized random forests and artificial neural networks on a small dataset of concrete containing nano SiO2 and RHA
Omolbanin Arasteh-Khoshbin, Seyed Morteza Seyedpour, Luis Mandl, et al.
European Journal of Environmental and Civil engineering (2024) Vol. 29, Iss. 2, pp. 331-350
Open Access
Predictive model for abdominal liposuction volume in patients with obesity using machine learning in a longitudinal multi-center study in Korea
Hyunji Sang, Jaeyu Park, Soeun Kim, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access
Experimental study on performance of Reinforced Concrete (RC) beams with varied proportions of fly ash
Roszaini Kadir, Pasala Venkata Satish, Snigdha Sushil, et al.
i-manager’s Journal on Structural Engineering (2024) Vol. 13, Iss. 1, pp. 1-1
Closed Access
Sentiment-Driven Forecasting LSTM Neural Networks for Stock Prediction-Case of China Bank Sector
Shangshang Jin
International Journal of Advanced Computer Science and Applications (2023) Vol. 14, Iss. 11
Open Access | Times Cited: 1

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