Dec 1, 2020 ¡¤ This study aims to develop machine learning based load prediction model for residential building, five machine-learning models have been utilised for the ...

In the present study, simple polynomial function is used to estimate the annual energy demand as a function of building envelope physical and geometric ...

This article presents a comparative analysis of two prominent machine learning techniques for predicting electricity consumption in workplace lighting systems.

Using SVM's as a method of building energy consumption regression has recently become popular in energy modeling literature (Ahmad et al. 2014). Ahmad ...

Dec 1, 2022 ¡¤ In this paper, a metamodel-based approach involving simulation data collection and data-driven techniques was used to forecast and optimize heating and cooling ...

Nov 10, 2020 ¡¤ Before applying the polynomial equation, first, we made four sets of couples from the given eight attributes, where each couple is expanding up ...

In this paper, we review the application of machine learning techniques in building load prediction under the organization and logic of the machine learning, ...

After simulation analysis, the accuracy of load forecasting based on 3-year history increases by 3.8%.

ZIP and exponential models are used to describe the electrical characteristics of the buildings' load model with most of the research focusing on residential ...

This research investigates various ML methods for predicting energy efficiency in buildings, with a particular emphasis on heating and cooling loads.