A review of artificial intelligence based building energy use prediction: Contrasting the capabilities of single and ensemble prediction models

By Zeyu Wang, R. Srinivasan. 2017

579 citations recorded by the source corpus.

Subfields: Building and Construction, Electrical and Electronic Engineering, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/7dad0b5251380bd828eb1f72c05ac04ab24cdc1f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Building and Construction

1. Benjamin C. M. Fung
2. Ying Sun
3. Tan Yigitcanlar
4. F. Haghighat

In Electrical and Electronic Engineering

1. Ali Fiaz
2. Benjamin C. M. Fung
3. Ali Ouni
4. Ying Sun
5. Mohamed Adel Serhani
6. Salah Bouktif
7. F. Haghighat

In Environmental Engineering

1. Benjamin C. M. Fung
2. Ying Sun
3. F. Haghighat

Citations in the corpus

• Contributions and Risks of Artificial Intelligence (AI) in Building Smarter Cities: Insights from a Systematic Review of the Literature (2020, background): “Environment PM ML PP NN DL Smart Transport Wang & Srinivasan [81] A review of artificial intelligencebased building energy use prediction Renewable and Sustainable Energy Reviews To better understand of the use of ensemble models for predicting building energy use.”
• A review of the-state-of-the-art in data-driven approaches for building energy prediction (2020, background): “Many existing literature reviews, such as references [15] and [13], focus mainly on time horizon; therefore, the effect of prediction steps (i.”
• Optimal Deep Learning LSTM Model for Electric Load Forecasting using Feature Selection and Genetic Algorithm: Comparison with Machine Learning Approaches † (2018, background): “The limitation of these models resides in their dependence on the availability and the accuracy of input information [11].”
• A Review of Artificial Intelligence (AI) in Education from 2010 to 2020 (2021, methodology): “As previous reviews about AI were conducted in the physical sciences [16, 17], the study aimed to conduct a review in the field of the social sciences.”
• Smarter eco-cities and their leading-edge artificial intelligence of things solutions for environmental sustainability: A comprehensive systematic review (2023, background): “Researchers and scholars like Akhter et al. [82], Alsadi and Khatib [183], Das et al. [83], Dawoud, Lin, and Okba [184], Khan et al. [84], Youssef, El-Telbany, and Zekry [185], and Wang and Srinivasan [186] have made contributions in this fi eld of study.”