Occupancy Prediction Using Differential Evolution Online Sequential Extreme Learning Machine Model

Occupancy Prediction Using Differential Evolution Online Sequential Extreme Learning Machine Model

Despite increasing energy efficiency requirements, the full potential of energy efficiency is still unlocked; many buildings in the EU tend to consume more energy than predicted. Gathering data and developing models to predict occupants’ behaviour is seen as the next frontier in sustainable design....

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Bibliographic Details
Main Authors: Jonas Bielskus, Violeta Motuzienė, Tatjana Vilutienė, Audrius Indriulionis
Format: Article
Language:English
Published: MDPI AG 2020-08-01
Series:Energies
Subjects:
open-space office
occupancy prediction
energy-performance gap
online sequential extreme learning machine
DE-OSELM method
differential evolution
Online Access:https://www.mdpi.com/1996-1073/13/15/4033

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https://www.mdpi.com/1996-1073/13/15/4033

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