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:

Towards developing a systematic knowledge trend for building energy consumption prediction
Qingyao Qiao, Akilu Yunusa‐Kaltungo, R. E. Edwards
Journal of Building Engineering (2020) Vol. 35, pp. 101967-101967
Open Access | Times Cited: 84

Showing 1-25 of 84 citing articles:

A systematic review of passive energy consumption optimisation strategy selection for buildings through multiple criteria decision-making techniques
Amirhossein Balali, Akilu Yunusa‐Kaltungo, R. E. Edwards
Renewable and Sustainable Energy Reviews (2022) Vol. 171, pp. 113013-113013
Closed Access | Times Cited: 78
An evolutionary deep learning model based on EWKM, random forest algorithm, SSA and BiLSTM for building energy consumption prediction
Lei Lei, Suola Shao, Lixia Liang
Energy (2023) Vol. 288, pp. 129795-129795
Closed Access | Times Cited: 40
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
Research on Real-Time Energy Consumption Prediction Method and Characteristics of Office Buildings Integrating Occupancy and Meteorological Data
Huihui Lian, Hsi-Hsien Wei, Xinyue Wang, et al.
Buildings (2025) Vol. 15, Iss. 3, pp. 404-404
Open Access | Times Cited: 1
Machine learning for energy performance prediction at the design stage of buildings
Razak Olu-Ajayi, Hafiz Alaka, Ismail Sulaimon, et al.
Energy Sustainable Development/Energy for sustainable development (2021) Vol. 66, pp. 12-25
Open Access | Times Cited: 67
Efficacy of incorporating PCM into the building envelope on the energy saving and AHU power usage in winter
Nidal H. Abu‐Hamdeh, Ammar A. Melaibari, Thamer‎ Alquthami, et al.
Sustainable Energy Technologies and Assessments (2021) Vol. 43, pp. 100969-100969
Closed Access | Times Cited: 59
A Systematic Review of the Extent to Which BIM Is Integrated into Operation and Maintenance
Dania K. Abideen, Akilu Yunusa‐Kaltungo, Patrick Manu, et al.
Sustainability (2022) Vol. 14, Iss. 14, pp. 8692-8692
Open Access | Times Cited: 39
Framework for standardising carbon neutrality in building projects
Judy Too, Obuks Ejohwomu, Felix Kin Peng Hui, et al.
Journal of Cleaner Production (2022) Vol. 373, pp. 133858-133858
Open Access | Times Cited: 38
A hybrid agent-based machine learning method for human-centred energy consumption prediction
Qingyao Qiao, Akilu Yunusa‐Kaltungo
Energy and Buildings (2023) Vol. 283, pp. 112797-112797
Open Access | Times Cited: 34
PSO-Stacking improved ensemble model for campus building energy consumption forecasting based on priority feature selection
Yisheng Cao, Gang Liu, Jianping Sun, et al.
Journal of Building Engineering (2023) Vol. 72, pp. 106589-106589
Closed Access | Times Cited: 32
Multi-period, multi-timescale stochastic optimization model for simultaneous capacity investment and energy management decisions for hybrid Micro-Grids with green hydrogen production under uncertainty
Sunwoo Kim, Yechan Choi, Joungho Park, et al.
Renewable and Sustainable Energy Reviews (2023) Vol. 190, pp. 114049-114049
Closed Access | Times Cited: 31
Applications of immersive technologies for occupational safety and health training and education: A systematic review
Akinloluwa Babalola, Patrick Manu, Clara Cheung, et al.
Safety Science (2023) Vol. 166, pp. 106214-106214
Open Access | Times Cited: 26
Temporal dynamic assessment of household energy consumption and carbon emissions in China: From the perspective of occupants
Shu Su, Yujie Ding, Guozhi Li, et al.
Sustainable Production and Consumption (2023) Vol. 37, pp. 142-155
Closed Access | Times Cited: 23
BIM Integration with XAI Using LIME and MOO for Automated Green Building Energy Performance Analysis
Abdul Mateen Khan, Muhammad Abubakar Tariq, Sardar Kashif Ur Rehman, et al.
Energies (2024) Vol. 17, Iss. 13, pp. 3295-3295
Open Access | Times Cited: 10
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: 9
Effects of examine the phase change material through applying the solar collectors: exergy analysis of an air handling unit equipped with the heat recovery unit
Mashhour A. Alazwari, Nidal H. Abu‐Hamdeh, Ahmed B. Khoshaim, et al.
Journal of Energy Storage (2021) Vol. 41, pp. 103002-103002
Closed Access | Times Cited: 46
Effects of Al2O3 and TiO2 nanoparticles in order to reduce the energy demand in the conventional buildings by integrating the solar collectors and phase change materials
Jie Zhang, S. Mohammad Sajadi, Chen Yang, et al.
Sustainable Energy Technologies and Assessments (2022) Vol. 52, pp. 102114-102114
Closed Access | Times Cited: 34
Feature selection strategy for machine learning methods in building energy consumption prediction
Qingyao Qiao, Akilu Yunusa‐Kaltungo, R. E. Edwards
Energy Reports (2022) Vol. 8, pp. 13621-13654
Closed Access | Times Cited: 34
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
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
Government pandemic response strategies for AEC enterprises: lessons from COVID-19
Salma Husna Zamani, Rahimi A. Rahman, Muhammad Ashraf Fauzi, et al.
Journal of Engineering Design and Technology (2022) Vol. 22, Iss. 3, pp. 690-717
Closed Access | Times Cited: 27
An interpretable multi-stage forecasting framework for energy consumption and CO2 emissions for the transportation sector
Qingyao Qiao, Hamidreza Eskandari, Hassan Saadatmand, et al.
Energy (2023) Vol. 286, pp. 129499-129499
Open Access | Times Cited: 16
A study of deep learning-based multi-horizon building energy forecasting
Zhongjun Ni, Chi Zhang, Magnus Karlsson, et al.
Energy and Buildings (2023) Vol. 303, pp. 113810-113810
Open Access | Times Cited: 16
Holistic performance assessment of gridshells: Methodological framework and applications to steel gridshells
Lorenzo Raffaele, Luca Bruno, Francesco Laccone, et al.
Journal of Building Engineering (2024) Vol. 90, pp. 109406-109406
Open Access | Times Cited: 5
Enhanced Electricity Forecasting for Smart Buildings Using a TCN‐Bi‐LSTM Deep Learning Model
Sandeep Kumar Gautam, V.K. Shrivastava, Sandeep S. Udmale
Expert Systems (2025) Vol. 42, Iss. 3
Closed Access
Page 1 - Next Page

Scroll to top