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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:

Nature-inspired metaheuristic ensemble model for forecasting energy consumption in residential buildings
Duc-Hoc Tran, Duc-Long Luong, Jui‐Sheng Chou
Energy (2019) Vol. 191, pp. 116552-116552
Closed Access | Times Cited: 100

Showing 1-25 of 100 citing articles:

A deep learning framework for building energy consumption forecast
Nivethitha Somu, M. R. Gauthama Raman, Krithi Ramamritham
Renewable and Sustainable Energy Reviews (2020) Vol. 137, pp. 110591-110591
Closed Access | Times Cited: 350
Deep learning for load forecasting with smart meter data: Online Adaptive Recurrent Neural Network
Mohammad Navid Fekri, Harsh Patel, Katarina Grolinger, et al.
Applied Energy (2020) Vol. 282, pp. 116177-116177
Closed Access | Times Cited: 259
Physical energy and data-driven models in building energy prediction: A review
Yongbao Chen, Mingyue Guo, Zhisen Chen, et al.
Energy Reports (2022) Vol. 8, pp. 2656-2671
Open Access | Times Cited: 214
Building energy prediction using artificial neural networks: A literature survey
Chujie Lu, Sihui Li, Zhengjun Lu
Energy and Buildings (2021) Vol. 262, pp. 111718-111718
Closed Access | Times Cited: 151
Electrical load-temperature CNN for residential load forecasting
Maryam Imani
Energy (2021) Vol. 227, pp. 120480-120480
Closed Access | Times Cited: 124
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: 79
Integrating artificial intelligence in energy transition: A comprehensive review
Qiang Wang, Yuanfan Li, Rongrong Li
Energy Strategy Reviews (2025) Vol. 57, pp. 101600-101600
Open Access | Times Cited: 25
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: 24
Short-term prediction of building energy consumption employing an improved extreme gradient boosting model: A case study of an intake tower
Hongfang Lü, Fei-Fei Cheng, Xin Ma, et al.
Energy (2020) Vol. 203, pp. 117756-117756
Closed Access | Times Cited: 110
A hybrid neuro-fuzzy inference system-based algorithm for time series forecasting applied to energy consumption prediction
Mohammed Ali Jallal, Aurora González-Vidal, Antonio Skármeta, et al.
Applied Energy (2020) Vol. 268, pp. 114977-114977
Closed Access | Times Cited: 84
Fully Biobased Photothermal Films and Coatings for Indoor Ultraviolet Radiation and Heat Management
Jinrong Liu, Adrián Moreno, Jian Chang, et al.
ACS Applied Materials & Interfaces (2022) Vol. 14, Iss. 10, pp. 12693-12702
Open Access | Times Cited: 47
Regression tree ensemble learning-based prediction of the heating and cooling loads of residential buildings
Nikhil Pachauri, Chang Wook Ahn
Building Simulation (2022) Vol. 15, Iss. 11, pp. 2003-2017
Closed Access | Times Cited: 40
Short-term energy consumption prediction method for educational buildings based on model integration
Wen‐Qiang Cao, Junqi Yu, Mengyao Chao, et al.
Energy (2023) Vol. 283, pp. 128580-128580
Closed Access | Times Cited: 32
Roles of Artificial Intelligence and Machine Learning in Enhancing Construction Processes and Sustainable Communities
Kayode O. Kazeem, Timothy O. Olawumi, Temidayo Oluwasola Osunsanmi
Buildings (2023) Vol. 13, Iss. 8, pp. 2061-2061
Open Access | Times Cited: 27
AI-Driven Innovations in Building Energy Management Systems: A Review of Potential Applications and Energy Savings
Dalia Mohammed Talat Ebrahim Ali, Violeta Motuzienė, Rasa Džiugaitė-Tumėnienė
Energies (2024) Vol. 17, Iss. 17, pp. 4277-4277
Open Access | Times Cited: 13
Energy consumption prediction of industrial HVAC systems using Bayesian Networks
Francesco Giuseppe Ciampi, Andrea Rega, Thierno Diallo, et al.
Energy and Buildings (2024) Vol. 309, pp. 114039-114039
Open Access | Times Cited: 12
An emission predictive system for CO and NOx from gas turbine based on ensemble machine learning approach
Nikhil Pachauri
Fuel (2024) Vol. 366, pp. 131421-131421
Closed Access | Times Cited: 9
Optimized neural network combined model based on the induced ordered weighted averaging operator for vegetable price forecasting
Bo Li, Junqi Ding, Zhengqing Yin, et al.
Expert Systems with Applications (2020) Vol. 168, pp. 114232-114232
Closed Access | Times Cited: 53
Building’s hourly electrical load prediction based on data clustering and ensemble learning strategy
Kangji Li, Jinxing Zhang, Chen Xu, et al.
Energy and Buildings (2022) Vol. 261, pp. 111943-111943
Closed Access | Times Cited: 38
FCDT-IWBOA-LSSVR: An innovative hybrid machine learning approach for efficient prediction of short-to-mid-term photovoltaic generation
Liang Lu, Tiecheng Su, Yuxiang Gao, et al.
Journal of Cleaner Production (2022) Vol. 385, pp. 135716-135716
Closed Access | Times Cited: 34
A Hybrid Short-Term Load Forecasting Approach for Individual Residential Customer
Xin Lin, Ramon Zamora, Craig Baguley, et al.
IEEE Transactions on Power Delivery (2022) Vol. 38, Iss. 1, pp. 26-37
Closed Access | Times Cited: 33
Forecasting of Electricity Consumption by Household Consumers Using Fuzzy Logic Based on the Development Plan of the Power System of the Republic of Tajikistan
Saidjon Tavarov, Павел Матренин, Murodbek Safaraliev, et al.
Sustainability (2023) Vol. 15, Iss. 4, pp. 3725-3725
Open Access | Times Cited: 18
Forecasting heating and cooling loads in residential buildings using machine learning: a comparative study of techniques and influential indicators
Behrouz Mehdizadeh Khorrami, Alireza Soleimani, Anna Pinnarelli, et al.
Asian Journal of Civil Engineering (2023) Vol. 25, Iss. 2, pp. 1163-1177
Open Access | Times Cited: 18
An innovative machine learning based on feed-forward artificial neural network and equilibrium optimization for predicting solar irradiance
Ting Xu, Mohammad Hosein Sabzalian, Ahmad Hammoud, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 7
Meta learning regression framework for energy consumption prediction in retrofitted buildings: A case study of South Korea
Anh Tuan Nguyen, Yonghan Ahn, Soyeon Park, et al.
Journal of Building Engineering (2024) Vol. 96, pp. 110403-110403
Closed Access | Times Cited: 7
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