Restrictions and alternatives for the development data-based energy prediction models in buildings located in tropical climate: Literature review

J Cárdenas-Rangel, J Jaramillo-Ibarra… - Building and …, 2024 - Elsevier
Abstract–Prediction of energy consumption in buildings is the process that allows estimating
the amount of energy consumed in a specific future period. Typically, a predicted energy …

Office building energy consumption forecast: Adaptive long short term memory networks driven by improved beluga whale optimization algorithm

Z Feng, J An, M Han, X Ji, X Zhang, C Wang… - Journal of Building …, 2024 - Elsevier
With the development of urbanization, buildings have become a major source of energy
consumption. This research uses a data-driven approach to achieve accurate building …

Forecasting building energy demand and on-site power generation for residential buildings using long and short-term memory method with transfer learning

D Kim, G Seomun, Y Lee, H Cho, K Chin, MH Kim - Applied Energy, 2024 - Elsevier
This study evaluates the effectiveness of the long and short-term (LSTM) implementation
with a particular emphasis on assessing the impact of transfer learning techniques in …

Development and calibration of apartment building energy model based on architectural and energy consumption characteristics

R Lee, D Kim, J Yoon, E Kang, H Cho, J Kim - Renewable and Sustainable …, 2024 - Elsevier
Building energy modeling is pivotal in achieving sustainable energy goals throughout a
building's design and operation. However, discrepancies often arise between actual energy …

Transfer learning integrating similarity analysis for short-term and long-term building energy consumption prediction

Z **ng, Y Pan, Y Yang, X Yuan, Y Liang, Z Huang - Applied energy, 2024 - Elsevier
Currently, building energy consumption prediction models are usually based on a large
amount of historical operational data in high demands of building operating hours and …

[HTML][HTML] Sustainability, emission trading system and carbon leakage: An approach based on neural networks and multicriteria analysis

I D'Adamo, M Gastaldi, C Hachem-Vermette… - Sustainable Operations …, 2023 - Elsevier
Two transitions, green and digital, are changing the operations and strategies of industrial
systems. At the same time, businesses are challenged to be globally competitive. Europe …

[HTML][HTML] CRISP-DM-Based Data-Driven Approach for Building Energy Prediction Utilizing Indoor and Environmental Factors

M Elkabalawy, A Al-Sakkaf, E Mohammed Abdelkader… - Sustainability, 2024 - mdpi.com
The significant energy consumption associated with the built environment demands
comprehensive energy prediction modelling. Leveraging their ability to capture intricate …

Analysis and prediction of energy consumption in office buildings with variable refrigerant flow systems: A case study

X Zhou, N Wang, J Zou, G Liu, X Zhuang… - Journal of Building …, 2024 - Elsevier
Accurately predicting building air-conditioning energy consumption is particularly important
for energy management. However, for small datasets, there is a lack of simple and effective …

[HTML][HTML] Predicting the energy consumption of commercial buildings based on deep forest model and its interpretability

G Zheng, Z Feng, M Jiang, L Tan, Z Wang - Buildings, 2023 - mdpi.com
Building energy assessment models are considered to be one of the most informative
methods in building energy efficiency design, and most of the current building energy …

Improving LSTM forecasting through ensemble learning: a comparative analysis of various models

Z Ahmad, V Shanmugasundaram, Biju… - International Journal of …, 2024 - Springer
Supply chain management involves managing the entire manufacturing process, from
purchasing supplies to delivering the final product. Demand forecasting helps businesses …