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