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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:

Gradient boosting machine for predicting return temperature of district heating system: A case study for residential buildings in Tianjin
Mingju Gong, Yin Bai, Juan Qin, et al.
Journal of Building Engineering (2019) Vol. 27, pp. 100950-100950
Closed Access | Times Cited: 79

Showing 1-25 of 79 citing articles:

CatBoost model and artificial intelligence techniques for corporate failure prediction
Sami Ben Jabeur, Cheima Gharib, Salma Mefteh‐Wali, et al.
Technological Forecasting and Social Change (2021) Vol. 166, pp. 120658-120658
Closed Access | Times Cited: 251
Groundwater level prediction using machine learning algorithms in a drought-prone area
Quoc Bao Pham, Manish Kumar, Fabio Di Nunno, et al.
Neural Computing and Applications (2022) Vol. 34, Iss. 13, pp. 10751-10773
Closed Access | Times Cited: 124
Load forecasting of district heating system based on Informer
Mingju Gong, Yin Zhao, Jiawang Sun, et al.
Energy (2022) Vol. 253, pp. 124179-124179
Closed Access | Times Cited: 114
Building energy consumption prediction using multilayer perceptron neural network-assisted models; comparison of different optimization algorithms
Sadegh Afzal, Behrooz M. Ziapour, Afshar Shokri, et al.
Energy (2023) Vol. 282, pp. 128446-128446
Closed Access | Times Cited: 102
Predicting compressive strength of high-performance concrete with high volume ground granulated blast-furnace slag replacement using boosting machine learning algorithms
Vimal Rathakrishnan, Salmia Beddu, Ali Najah Ahmed
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 71
Improving the prediction of heating energy consumed at residential buildings using a combination of support vector regression and meta-heuristic algorithms
Hamed Khajavi, Amir Rastgoo
Energy (2023) Vol. 272, pp. 127069-127069
Closed Access | Times Cited: 52
Residential building energy consumption estimation: A novel ensemble and hybrid machine learning approach
Behnam Sadaghat, Sadegh Afzal, Ali Javadzade Khiavi
Expert Systems with Applications (2024) Vol. 251, pp. 123934-123934
Closed Access | Times Cited: 17
Predicting Daily Heating Energy Consumption in Residential Buildings through Integration of Random Forest Model and Meta-Heuristic Algorithms
Weiyan Xu, Jielei Tu, Ning Xu, et al.
Energy (2024) Vol. 301, pp. 131726-131726
Closed Access | Times Cited: 16
A new artificial intelligence strategy for predicting the groundwater level over the Rafsanjan aquifer in Iran
Ahmad Sharafati, Seyed Babak Haji Seyed Asadollah, Aminreza Neshat
Journal of Hydrology (2020) Vol. 591, pp. 125468-125468
Closed Access | Times Cited: 93
Evaluating the predictive power of different machine learning algorithms for groundwater salinity prediction of multi-layer coastal aquifers in the Mekong Delta, Vietnam
Dang An Tran, Maki Tsujimura, Nam Thang Ha, et al.
Ecological Indicators (2021) Vol. 127, pp. 107790-107790
Open Access | Times Cited: 91
Application of newly developed ensemble machine learning models for daily suspended sediment load prediction and related uncertainty analysis
Ahmad Sharafati, Seyed Babak Haji Seyed Asadollah, Davide Motta, et al.
Hydrological Sciences Journal (2020) Vol. 65, Iss. 12, pp. 2022-2042
Open Access | Times Cited: 90
Data mining with 12 machine learning algorithms for predict costs and carbon dioxide emission in integrated energy-water optimization model in buildings
Majid Emami Javanmard, S.F. Ghaderi, Mohamad Hoseinzadeh
Energy Conversion and Management (2021) Vol. 238, pp. 114153-114153
Closed Access | Times Cited: 63
Biochar and Application of Machine Learning: A Review
Kingsley Ukoba, Tien‐Chien Jen
IntechOpen eBooks (2022)
Open Access | Times Cited: 37
Building energy consumption prediction and optimization using different neural network-assisted models; comparison of different networks and optimization algorithms
Sadegh Afzal, Afshar Shokri, Behrooz M. Ziapour, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 127, pp. 107356-107356
Closed Access | Times Cited: 36
Implementing ensemble learning models for the prediction of shear strength of soil
Ahsan Rabbani, Pijush Samui, Sunita Kumari
Asian Journal of Civil Engineering (2023) Vol. 24, Iss. 7, pp. 2103-2119
Closed Access | Times Cited: 25
Time Series Forecasting and Modeling of Food Demand Supply Chain Based on Regressors Analysis
Sandeep Kumar Panda, Sachi Nandan Mohanty
IEEE Access (2023) Vol. 11, pp. 42679-42700
Open Access | Times Cited: 24
A collaborative privacy-preserving approach for passenger demand forecasting of autonomous taxis empowered by federated learning in smart cities
Adeel Munawar, Mongkut Piantanakulchai
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 10
Machine learning-enabled estimation of crosswind load effect on tall buildings
Pengfei Lin, Fei Ding, Gang Hu, et al.
Journal of Wind Engineering and Industrial Aerodynamics (2021) Vol. 220, pp. 104860-104860
Open Access | Times Cited: 50
Estimation of modified expansive soil CBR with multivariate adaptive regression splines, random forest and gradient boosting machine
Chijioke Christopher Ikeagwuani
Innovative Infrastructure Solutions (2021) Vol. 6, Iss. 4
Closed Access | Times Cited: 43
Toward explainable electrical load forecasting of buildings: A comparative study of tree-based ensemble methods with Shapley values
Jihoon Moon, Seungmin Rho, Sung Wook Baik
Sustainable Energy Technologies and Assessments (2022) Vol. 54, pp. 102888-102888
Open Access | Times Cited: 33
Optimisation of thermal comfort and indoor air quality estimations applied to in-use buildings combining NSGA-III and XGBoost
Miguel Martínez-Comesaña, Pablo Eguía, Javier Martínez Martínez, et al.
Sustainable Cities and Society (2022) Vol. 80, pp. 103723-103723
Open Access | Times Cited: 32
Real-time pavement temperature prediction through ensemble machine learning
Yared Bitew Kebede, Ming‐Der Yang, Chien-Wei Huang
Engineering Applications of Artificial Intelligence (2024) Vol. 135, pp. 108870-108870
Open Access | Times Cited: 5
Motor imagery based brain-computer interface: improving the EEG classification using Delta rhythm and LightGBM algorithm
Said Abenna, Mohammed Nahid, Abderrahim Bajit
Biomedical Signal Processing and Control (2021) Vol. 71, pp. 103102-103102
Closed Access | Times Cited: 32
A novel combined model for heat load prediction in district heating systems
Yanmin Wang, Zhiwei Li, Junjie Liu, et al.
Applied Thermal Engineering (2023) Vol. 227, pp. 120372-120372
Closed Access | Times Cited: 15
Modeling Viscosity of CO2–N2 Gaseous Mixtures Using Robust Tree-Based Techniques: Extra Tree, Random Forest, GBoost, and LightGBM
Haimin Zheng, Atena Mahmoudzadeh, Behnam Amiri-Ramsheh, et al.
ACS Omega (2023) Vol. 8, Iss. 15, pp. 13863-13875
Open Access | Times Cited: 13
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