Published October 2003 | Version v1
Journal article

Application of artificial neural network to predict the optimal start time for heating system in building

Description

The artificial neural network (ANN) approach is a generic technique for mapping non-linear relationships between inputs and outputs without knowing the details of these relationships. This paper presents an application of the ANN in a building control system. The objective of this study is to develop an optimized ANN model to determine the optimal start time for a heating system in a building. For this, programs for predicting the room air temperature and the learning of the ANN model based on back propagation learning were developed, and learning data for various building conditions were collected through program simulation for predicting the room air temperature using systems of experimental design. Then, the optimized ANN model was presented through learning of the ANN, and its performance to determine the optimal start time was evaluated

Additional details

Identifiers

PII
S019689040300044X;

Publishing Information

Journal Title
Energy Conversion and Management
Journal Volume
44
Journal Issue
17
Journal Page Range
p. 2791-2809
ISSN
0196-8904
CODEN
ECMADL

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
35000626
Subject category
S99: GENERAL AND MISCELLANEOUS; S42: ENGINEERING;
Descriptors DEI
AMBIENT TEMPERATURE; BUILDINGS; HEATING SYSTEMS; NEURAL NETWORKS; NONLINEAR PROBLEMS; OPTIMIZATION; START-UP
Descriptors DEC
ENERGY SYSTEMS

Optional Information

Copyright
Copyright (c) 2003 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.