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Jun 7, 2024This article presents a comparative analysis of two prominent machine learning techniques for predicting electricity consumption in workplace lighting systems.
Sep 23, 2024This study employs machine learning methods containing Support Vector Regression, Extreme Gradient Boosting, and a Dempster-Shafer Theory-based ensemble model.
Dec 1, 2023We propose a novel method for probabilistic forecasting of the total load of a residential community and its base and thermal components.
Oct 18, 2024This study introduces an advanced mathematical methodology for predicting energy generation and consumption based on temperature variations.
Mar 1, 2024This study presents a data-driven predictive control method with time-series forecasting (TSF) and reinforcement learning (RL), to examine various sensor ...
Aug 25, 2024The objective of this study is to evaluate and validate Bromilow's time-cost model and Love et al.'s time-floor model to estimate early project durations.
Missing: Load | Show results with:Load
Jun 13, 2024This paper presents an approach for improving the accuracy of energy consumption estimate during early design stage for residential buildings.
Oct 16, 2024This study presents a machine learning application for generating synthetic building electrical load profiles. The implementation followed the Cross Industry ...
Missing: Function | Show results with:Function
Mar 4, 2024It fits the curve using a polynomial equation for maximum accuracy while avoiding over-fit or under-fit [58]. One of the primary advantages of the MPR model ...
Jan 23, 2024Abstract: Increasing building energy consumption has led to environmental and economic issues. Energy demand prediction (DP) aims to reduce energy use.