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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:

Deep-learning neural-network architectures and methods: Using component-based models in building-design energy prediction
Sundaravelpandian Singaravel, Johan A. K. Suykens, Philipp Geyer
Advanced Engineering Informatics (2018) Vol. 38, pp. 81-90
Open Access | Times Cited: 206

Showing 1-25 of 206 citing articles:

Comparing the prediction performance of a Deep Learning Neural Network model with conventional machine learning models in landslide susceptibility assessment
Dieu Tien Bui, Paraskevas Tsangaratos, Viet-Tien Nguyen, et al.
CATENA (2020) Vol. 188, pp. 104426-104426
Closed Access | Times Cited: 378
Deep learning in the construction industry: A review of present status and future innovations
Taofeek Akinosho, Lukumon O. Oyedele, Muhammad Bilal, et al.
Journal of Building Engineering (2020) Vol. 32, pp. 101827-101827
Open Access | Times Cited: 365
IoT-enabled smart appliances under industry 4.0: A case study
Shohin Aheleroff, Xun Xu, Yuqian Lu, et al.
Advanced Engineering Informatics (2020) Vol. 43, pp. 101043-101043
Closed Access | Times Cited: 264
Surrogate modelling for sustainable building design – A review
Paul Westermann, Ralph Evins
Energy and Buildings (2019) Vol. 198, pp. 170-186
Closed Access | Times Cited: 223
Forecasting Energy Use in Buildings Using Artificial Neural Networks: A Review
Jason Runge, Radu Zmeureanu
Energies (2019) Vol. 12, Iss. 17, pp. 3254-3254
Open Access | Times Cited: 209
Transfer learning for smart buildings: A critical review of algorithms, applications, and future perspectives
Giuseppe Pinto, Zhe Wang, Abhishek Roy, et al.
Advances in Applied Energy (2022) Vol. 5, pp. 100084-100084
Open Access | Times Cited: 184
Biomedical data and computational models for drug repositioning: a comprehensive review
Huimin Luo, Min Li, Mengyun Yang, et al.
Briefings in Bioinformatics (2020) Vol. 22, Iss. 2, pp. 1604-1619
Closed Access | Times Cited: 159
Predictive model-based quality inspection using Machine Learning and Edge Cloud Computing
Jacqueline Schmitt, Jochen Bönig, Thorbjörn Borggräfe, et al.
Advanced Engineering Informatics (2020) Vol. 45, pp. 101101-101101
Open Access | Times Cited: 150
Application and characterization of metamodels based on artificial neural networks for building performance simulation: A systematic review
Nadia D. Román, Facundo Bre, Vı́ctor D. Fachinotti, et al.
Energy and Buildings (2020) Vol. 217, pp. 109972-109972
Closed Access | Times Cited: 137
Machine Learning and Deep Learning Methods for Enhancing Building Energy Efficiency and Indoor Environmental Quality – A Review
Paige Wenbin Tien, Shuangyu Wei, Jo Darkwa, et al.
Energy and AI (2022) Vol. 10, pp. 100198-100198
Open Access | Times Cited: 135
Forecasting building energy consumption: Adaptive long-short term memory neural networks driven by genetic algorithm
Xiaojun Luo, Lukumon O. Oyedele
Advanced Engineering Informatics (2021) Vol. 50, pp. 101357-101357
Closed Access | Times Cited: 113
Buildings' energy consumption prediction models based on buildings’ characteristics: Research trends, taxonomy, and performance measures
Amal A. Al-Shargabi, Abdulbasit Almhafdy, Dina M. Ibrahim, et al.
Journal of Building Engineering (2022) Vol. 54, pp. 104577-104577
Closed Access | Times Cited: 74
Energy modelling and control of building heating and cooling systems with data-driven and hybrid models—A review
Yasaman Balali, Adrian Chong, Andrew Busch, et al.
Renewable and Sustainable Energy Reviews (2023) Vol. 183, pp. 113496-113496
Open Access | Times Cited: 48
Hybrid data-driven and physics-based fast building cooling demand modeling method for large-scale building demand response control
Chenxin Feng, Chaobo Zhang, Jie Lu, et al.
Journal of Building Engineering (2025) Vol. 100, pp. 111808-111808
Closed Access | Times Cited: 1
Multi-objective optimization design of a complex building based on an artificial neural network and performance evaluation of algorithms
Binghui Si, Jianguo Wang, Xinyue Yao, et al.
Advanced Engineering Informatics (2019) Vol. 40, pp. 93-109
Closed Access | Times Cited: 137
Effectiveness assessment of Keras based deep learning with different robust optimization algorithms for shallow landslide susceptibility mapping at tropical area
Viet‐Ha Nhu, Nhat‐Duc Hoang, Hieu Nguyen, et al.
CATENA (2020) Vol. 188, pp. 104458-104458
Closed Access | Times Cited: 136
Deep learning model for Demolition Waste Prediction in a circular economy
Lukman Akanbi, Ahmed Oyedele, Lukumon O. Oyedele, et al.
Journal of Cleaner Production (2020) Vol. 274, pp. 122843-122843
Closed Access | Times Cited: 134
On the assessment and control optimisation of demand response programs in residential buildings
Fabiano Pallonetto, Маттиа Де Роса, Francesco D’Ettorre, et al.
Renewable and Sustainable Energy Reviews (2020) Vol. 127, pp. 109861-109861
Open Access | Times Cited: 127
Feature extraction and genetic algorithm enhanced adaptive deep neural network for energy consumption prediction in buildings
Xiaojun Luo, Lukumon O. Oyedele, Anuoluwapo Ajayi, et al.
Renewable and Sustainable Energy Reviews (2020) Vol. 131, pp. 109980-109980
Open Access | Times Cited: 122
A Novel Artificial Intelligence Approach to Predict Blast-Induced Ground Vibration in Open-Pit Mines Based on the Firefly Algorithm and Artificial Neural Network
Yonghui Shang, Hoang Nguyen, Xuan-Nam Bui, et al.
Natural Resources Research (2019) Vol. 29, Iss. 2, pp. 723-737
Closed Access | Times Cited: 113
Component-based machine learning for performance prediction in building design
Philipp Geyer, Sundaravelpandian Singaravel
Applied Energy (2018) Vol. 228, pp. 1439-1453
Open Access | Times Cited: 106
Carbon futures price forecasting based with ARIMA-CNN-LSTM model
Lei Ji, Yingchao Zou, Kaijian He, et al.
Procedia Computer Science (2019) Vol. 162, pp. 33-38
Open Access | Times Cited: 106
Practical issues in implementing machine-learning models for building energy efficiency: Moving beyond obstacles
Zeyu Wang, Jian Liu, Yuanxin Zhang, et al.
Renewable and Sustainable Energy Reviews (2021) Vol. 143, pp. 110929-110929
Closed Access | Times Cited: 91
Integrating BIM with building performance analysis in project life-cycle
Ruoyu Jin, Botao Zhong, Ling Ma, et al.
Automation in Construction (2019) Vol. 106, pp. 102861-102861
Open Access | Times Cited: 86
Machine-learning based study on the on-site renewable electrical performance of an optimal hybrid PCMs integrated renewable system with high-level parameters’ uncertainties
Yuekuan Zhou, Siqian Zheng, Guoqiang Zhang
Renewable Energy (2019) Vol. 151, pp. 403-418
Closed Access | Times Cited: 83
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