Comparative study of machine learning-based multi-objective prediction framework for multiple building energy loads-Reference-Cited by-同舟云学术

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Comparative study of machine learning-based multi-objective prediction framework for multiple building energy loads

Published:2020-10 Issue: Volume:61 Page:102283
ISSN:2210-6707
Container-title:Sustainable Cities and Society
language:en
Short-container-title:Sustainable Cities and Society

Author:

Luo X.J.,Oyedele Lukumon O.,Ajayi Anuoluwapo O.,Akinade Olugbenga O.

Funder

The UK Department for Business, Energy & Industrial Strategy

Publisher

Elsevier BV

Subject

Transportation,Renewable Energy, Sustainability and the Environment,Civil and Structural Engineering,Geography, Planning and Development

Reference67 articles.

1. Short and medium-term forecasting of cooling and heating load load in building environment with data-mining based approaches;Ahmad;Energy and Buildings,2018

2. Deployment of data-mining short and medium-term horizon cooling load forecasting models for building energy optimization and management;Ahmad;International Journal of Refrigeration,2019

3. Simulation of energy consumption for Kuwaiti domestic buildings;Al-ajmi;Energy and Buildings,2008

4. Smart windows—Dynamic control of building energy performance;Allen;Energy and Buildings,2017

5. PV power forecast using a nonparametric PV model;Almeida;Solar Energy,2015

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4. Enhanced building energy harvesting through integrated piezoelectric materials and smart road traffic routing;Letters in Spatial and Resource Sciences;2024-09-09

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