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Jun 7, 2024 , This article presents a comparative analysis of two prominent machine learning techniques for predicting electricity consumption in workplace lighting systems.
Sep 23, 2024 , This study employs machine learning methods containing Support Vector Regression, Extreme Gradient Boosting, and a Dempster-Shafer Theory-based ensemble model.
Dec 1, 2023 , We propose a novel method for probabilistic forecasting of the total load of a residential community and its base and thermal components.
Oct 18, 2024 , This study introduces an advanced mathematical methodology for predicting energy generation and consumption based on temperature variations.
Mar 1, 2024 , This study presents a data-driven predictive control method with time-series forecasting (TSF) and reinforcement learning (RL), to examine various sensor ...
Aug 25, 2024 , The 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, 2024 , This paper presents an approach for improving the accuracy of energy consumption estimate during early design stage for residential buildings.
Oct 16, 2024 , This 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, 2024 , It 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, 2024 , Abstract: Increasing building energy consumption has led to environmental and economic issues. Energy demand prediction (DP) aims to reduce energy use.