Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

A novel improved model for building energy consumption prediction based on model integration
Ran Wang, Shilei Lu, Wei Feng
Applied Energy (2020) Vol. 262, pp. 114561-114561
Open Access | Times Cited: 182

Showing 26-50 of 182 citing articles:

Investigating the application of a commercial and residential energy consumption prediction model for urban Planning scenarios with Machine Learning and Shapley Additive explanation methods
Shideh Shams Amiri, Maya Mueller, Simi Hoque
Energy and Buildings (2023) Vol. 287, pp. 112965-112965
Open Access | Times Cited: 27
Data-Driven Energy Consumption Prediction of a University Office Building using Machine Learning Algorithms
Hasan Yeşilyurt, Yeşim DOKUZ, Ahmet Şakir Dokuz
Energy (2024), pp. 133242-133242
Closed Access | Times Cited: 8
Application and evaluation of the evolutionary algorithms combined with conventional neural network to determine the building energy consumption of the residential sector
Guimei Wang, Azfarizal Mukhtar, Hossein Moayedi, et al.
Energy (2024) Vol. 298, pp. 131312-131312
Closed Access | Times Cited: 7
Multiple Electric Energy Consumption Forecasting Using a Cluster-Based Strategy for Transfer Learning in Smart Building
Tuong Le, Minh Thanh Vo, Tung Kieu, et al.
Sensors (2020) Vol. 20, Iss. 9, pp. 2668-2668
Open Access | Times Cited: 66
Forecasting Natural Gas Production and Consumption in United States-Evidence from SARIMA and SARIMAX Models
Palanisamy Manigandan, Md Shabbir Alam, Majed Alharthi, et al.
Energies (2021) Vol. 14, Iss. 19, pp. 6021-6021
Open Access | Times Cited: 54
Heating and Cooling Loads Forecasting for Residential Buildings Based on Hybrid Machine Learning Applications: A Comprehensive Review and Comparative Analysis
Arash Moradzadeh, Behnam Mohammadi‐Ivatloo, Mehdi Abapour, et al.
IEEE Access (2021) Vol. 10, pp. 2196-2215
Open Access | Times Cited: 53
A novel deep generative modeling-based data augmentation strategy for improving short-term building energy predictions
Cheng Fan, Meiling Chen, Rui Tang, et al.
Building Simulation (2021) Vol. 15, Iss. 2, pp. 197-211
Closed Access | Times Cited: 47
Smart and intelligent energy monitoring systems: A comprehensive literature survey and future research guidelines
Tanveer Hussain, Fath U Min Ullah, Khan Muhammad, et al.
International Journal of Energy Research (2021) Vol. 45, Iss. 3, pp. 3590-3614
Closed Access | Times Cited: 46
Federated learning-based short-term building energy consumption prediction method for solving the data silos problem
Junyang Li, Chaobo Zhang, Yang Zhao, et al.
Building Simulation (2021) Vol. 15, Iss. 6, pp. 1145-1159
Closed Access | Times Cited: 45
Energy consumption prediction of appliances using machine learning and multi-objective binary grey wolf optimization for feature selection
Dorin Moldovan, Adam Słowik
Applied Soft Computing (2021) Vol. 111, pp. 107745-107745
Closed Access | Times Cited: 44
Household Energy Consumption Prediction Using the Stationary Wavelet Transform and Transformers
Lyes Saad Saoud, Hasan Al-Marzouqi, Ramy Hussein
IEEE Access (2022) Vol. 10, pp. 5171-5183
Open Access | Times Cited: 33
A two-step strategy for fuel consumption prediction and optimization of ocean-going ships
Zhihui Hu, Tianrui Zhou, Zhen Rong, et al.
Ocean Engineering (2022) Vol. 249, pp. 110904-110904
Closed Access | Times Cited: 29
Prediction of energy use intensity of urban buildings using the semi-supervised deep learning model
Feifeng Jiang, Jun Ma, Zheng Li, et al.
Energy (2022) Vol. 249, pp. 123631-123631
Closed Access | Times Cited: 29
An ensemble learning-based framework for assessing the energy flexibility of residential buildings with multicomponent energy systems
Adamantios Bampoulas, Fabiano Pallonetto, Eleni Mangina, et al.
Applied Energy (2022) Vol. 315, pp. 118947-118947
Open Access | Times Cited: 29
Effect of physical, environmental, and social factors on prediction of building energy consumption for public buildings based on real-world big data
Yuhang Zhang, Yi Zhang, Yi Zhang, et al.
Energy (2022) Vol. 261, pp. 125286-125286
Closed Access | Times Cited: 28
An artificial intelligence (AI)-driven method for forecasting cooling and heating loads in office buildings by integrating building thermal load characteristics
Jing Zhao, Xiulian Yuan, Yaoqi Duan, et al.
Journal of Building Engineering (2023) Vol. 79, pp. 107855-107855
Closed Access | Times Cited: 20
Grey-box and ANN-based building models for multistep-ahead prediction of indoor temperature to implement model predictive control
Abu Talib, Semi Park, Piljae Im, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 126, pp. 107115-107115
Closed Access | Times Cited: 16
Model predictive control for the ice-storage air-conditioning system coupled with multi-objective optimization
Jing Zhao, Dehan Liu, Xiulian Yuan, et al.
Applied Thermal Engineering (2024) Vol. 243, pp. 122595-122595
Closed Access | Times Cited: 7
Hourly load prediction based feature selection scheme and hybrid CNN‐LSTM method for building's smart solar microgrid
Thao Nguyen Da, Ming‐Yuan Cho, Phuong Nguyen Thanh
Expert Systems (2024) Vol. 41, Iss. 7
Closed Access | Times Cited: 6
A novel method of fuel consumption prediction for wing-diesel hybrid ships based on high-dimensional feature selection and improved blending ensemble learning method
Tian Lan, Lianzhong Huang, Ranqi Ma, et al.
Ocean Engineering (2024) Vol. 307, pp. 118156-118156
Closed Access | Times Cited: 6
Advancing building energy efficiency: A deep learning approach to early-stage prediction of residential electric consumption
Karthic Sundaram, K. R. Sri Preethaa, Yuvaraj Natarajan, et al.
Energy Reports (2024) Vol. 12, pp. 1281-1292
Closed Access | Times Cited: 6
More Accurate Prediction of Oxygen Transfer in Water through Venturi Flumes by Data Analysis, Machine Learning, and Uncertainty Investigation
N. K. Tiwari, Dinesh Panwar
Journal of Environmental Engineering (2025) Vol. 151, Iss. 3
Closed Access
Novel deep neural network architecture fusion to simultaneously predict short-term and long-term energy consumption
Abrar Ahmed, Safdar Ali, Ali Raza, et al.
PLoS ONE (2025) Vol. 20, Iss. 1, pp. e0315668-e0315668
Open Access
Predicting Energy Consumption of Residential Buildings Using Metaheuristic-optimized Artificial Neural Network Technique in Early Design Stage
Mosbeh R. Kaloop, Furquan Ahmad, Pijush Samui, et al.
Building and Environment (2025), pp. 112749-112749
Closed Access
A Secure Federated Deep Learning-Based Approach for Heating Load Demand Forecasting in Building Environment
Arash Moradzadeh, Hamed Moayyed, Behnam Mohammadi‐Ivatloo, et al.
IEEE Access (2021) Vol. 10, pp. 5037-5050
Open Access | Times Cited: 32

Scroll to top