Applying artificial neural networks to promote behaviour change for saving residential energy

Yaqub Rafiq; Shen Wei; Robert Guest; Robert Stone; Pieter De Wilde

Applying artificial neural networks to promote behaviour change for saving residential energy

Yaqub Rafiq^*, Shen Wei, Robert Guest, Robert Stone, Pieter De Wilde

^*Corresponding author for this work

Electronic, Electrical and Systems Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

In this paper Artificial Neural Networks (ANNs) is used to model effects of various human behaviour on energy consumption of the residential buildings in the UK. A virtual model of a bungalow has been developed in which various aspects of the, physical changes in the building such as wall and floor insulation, single and double glazing combined by the human behaviour aspects such as thermostat setting, various periods of door and/or window opening etc. are modelled using EnergyPlus software for evaluating energy consumption for a combination of scenarios. ANNs were then used to learn the effects of various human behaviours on energy consumption. The results demonstrated that the ANN is capable of learning the effects that changes in the human behaviour have in evaluating energy saving in residential buildings and it generated results very quickly for unseen cases.

Original language	English
Title of host publication	Proceedings of the International Workshop on Artificial Neural Networks and Intelligent Information Processing, ANNIIP 2014 - In Conjunction with ICINCO 2014
Publisher	SciTePress
Pages	3-10
Number of pages	8
ISBN (Electronic)	9789897580413
Publication status	Published - 1 Jan 2014
Event	International Workshop on Artificial Neural Networks and Intelligent Information Processing, ANNIIP 2014 - In Conjuction with the International Conference on Informatics in Control, Automation and Robotics, ICINCO 2014 - Vienna, Austria Duration: 1 Sept 2014 → 3 Sept 2014

Conference

Conference	International Workshop on Artificial Neural Networks and Intelligent Information Processing, ANNIIP 2014 - In Conjuction with the International Conference on Informatics in Control, Automation and Robotics, ICINCO 2014
Country/Territory	Austria
City	Vienna
Period	1/09/14 → 3/09/14

ASJC Scopus subject areas

Artificial Intelligence
Information Systems

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Cite this

@inproceedings{25f1c8b53da946e2a2dce475e56ed35b,

title = "Applying artificial neural networks to promote behaviour change for saving residential energy",

abstract = "In this paper Artificial Neural Networks (ANNs) is used to model effects of various human behaviour on energy consumption of the residential buildings in the UK. A virtual model of a bungalow has been developed in which various aspects of the, physical changes in the building such as wall and floor insulation, single and double glazing combined by the human behaviour aspects such as thermostat setting, various periods of door and/or window opening etc. are modelled using EnergyPlus software for evaluating energy consumption for a combination of scenarios. ANNs were then used to learn the effects of various human behaviours on energy consumption. The results demonstrated that the ANN is capable of learning the effects that changes in the human behaviour have in evaluating energy saving in residential buildings and it generated results very quickly for unseen cases.",

author = "Yaqub Rafiq and Shen Wei and Robert Guest and Robert Stone and {De Wilde}, Pieter",

year = "2014",

month = jan,

day = "1",

language = "English",

pages = "3--10",

booktitle = "Proceedings of the International Workshop on Artificial Neural Networks and Intelligent Information Processing, ANNIIP 2014 - In Conjunction with ICINCO 2014",

publisher = "SciTePress",

note = "International Workshop on Artificial Neural Networks and Intelligent Information Processing, ANNIIP 2014 - In Conjuction with the International Conference on Informatics in Control, Automation and Robotics, ICINCO 2014 ; Conference date: 01-09-2014 Through 03-09-2014",

}

Rafiq, Y, Wei, S, Guest, R, Stone, R & De Wilde, P 2014, Applying artificial neural networks to promote behaviour change for saving residential energy. in Proceedings of the International Workshop on Artificial Neural Networks and Intelligent Information Processing, ANNIIP 2014 - In Conjunction with ICINCO 2014. SciTePress, pp. 3-10, International Workshop on Artificial Neural Networks and Intelligent Information Processing, ANNIIP 2014 - In Conjuction with the International Conference on Informatics in Control, Automation and Robotics, ICINCO 2014, Vienna, Austria, 1/09/14.

Applying artificial neural networks to promote behaviour change for saving residential energy. / Rafiq, Yaqub; Wei, Shen; Guest, Robert et al.
Proceedings of the International Workshop on Artificial Neural Networks and Intelligent Information Processing, ANNIIP 2014 - In Conjunction with ICINCO 2014. SciTePress, 2014. p. 3-10.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Applying artificial neural networks to promote behaviour change for saving residential energy

AU - Rafiq, Yaqub

AU - Wei, Shen

AU - Guest, Robert

AU - Stone, Robert

AU - De Wilde, Pieter

PY - 2014/1/1

Y1 - 2014/1/1

N2 - In this paper Artificial Neural Networks (ANNs) is used to model effects of various human behaviour on energy consumption of the residential buildings in the UK. A virtual model of a bungalow has been developed in which various aspects of the, physical changes in the building such as wall and floor insulation, single and double glazing combined by the human behaviour aspects such as thermostat setting, various periods of door and/or window opening etc. are modelled using EnergyPlus software for evaluating energy consumption for a combination of scenarios. ANNs were then used to learn the effects of various human behaviours on energy consumption. The results demonstrated that the ANN is capable of learning the effects that changes in the human behaviour have in evaluating energy saving in residential buildings and it generated results very quickly for unseen cases.

AB - In this paper Artificial Neural Networks (ANNs) is used to model effects of various human behaviour on energy consumption of the residential buildings in the UK. A virtual model of a bungalow has been developed in which various aspects of the, physical changes in the building such as wall and floor insulation, single and double glazing combined by the human behaviour aspects such as thermostat setting, various periods of door and/or window opening etc. are modelled using EnergyPlus software for evaluating energy consumption for a combination of scenarios. ANNs were then used to learn the effects of various human behaviours on energy consumption. The results demonstrated that the ANN is capable of learning the effects that changes in the human behaviour have in evaluating energy saving in residential buildings and it generated results very quickly for unseen cases.

UR - http://www.scopus.com/inward/record.url?scp=84908871319&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:84908871319

SP - 3

EP - 10

BT - Proceedings of the International Workshop on Artificial Neural Networks and Intelligent Information Processing, ANNIIP 2014 - In Conjunction with ICINCO 2014

PB - SciTePress

T2 - International Workshop on Artificial Neural Networks and Intelligent Information Processing, ANNIIP 2014 - In Conjuction with the International Conference on Informatics in Control, Automation and Robotics, ICINCO 2014

Y2 - 1 September 2014 through 3 September 2014

ER -

Applying artificial neural networks to promote behaviour change for saving residential energy

Abstract

Conference

ASJC Scopus subject areas

UN SDGs

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Cite this