Artificial neural network for the control of the openings and cooling systems of the double skin envelope buildings

Jin Woo Moon, Sooyoung Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

This study aimed at developing an artificial neural network (ANN)-based temperature control method for the double skin envelope buildings. For this, control logic for opening conditions of the inner and outer surfaces' openings as well as for cooling system's operation was developed based on the predictive and adaptive ANN model. The parametrical optimization process for the structure and learning methods of the ANN model was conducted in terms of the number of hidden layers, the number of neurons in the hidden layers, learning rate, and moment. Then, the performance of this optimized model was tested using the similarity analysis between the predicted values from the ANN model and the measured values from the actual double skin envelope building. Analysis revealed that the developed ANN model proved its prediction accuracy and adaptability in terms of stable Root Mean Square (RMS) and Mean Square Error (MSE) values. Based on this finding, it can be concluded that the developed ANN model showed potentials to be successfully applied to the temperature controls for the double skin envelope buildings.

Original languageEnglish
Title of host publicationProgress in Environmental Science and Engineering
Pages2859-2865
Number of pages7
DOIs
Publication statusPublished - 2013 Jan 8
Event2nd International Conference on Energy, Environment and Sustainable Development, EESD 2012 - Jilin, China
Duration: 2012 Oct 122012 Oct 14

Publication series

NameAdvanced Materials Research
Volume610-613
ISSN (Print)1022-6680

Other

Other2nd International Conference on Energy, Environment and Sustainable Development, EESD 2012
CountryChina
CityJilin
Period12/10/1212/10/14

Fingerprint

Cooling systems
Skin
Neural networks
Temperature control
Mean square error
Neurons

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Cite this

Moon, J. W., & Kim, S. (2013). Artificial neural network for the control of the openings and cooling systems of the double skin envelope buildings. In Progress in Environmental Science and Engineering (pp. 2859-2865). (Advanced Materials Research; Vol. 610-613). https://doi.org/10.4028/www.scientific.net/AMR.610-613.2859
Moon, Jin Woo ; Kim, Sooyoung. / Artificial neural network for the control of the openings and cooling systems of the double skin envelope buildings. Progress in Environmental Science and Engineering. 2013. pp. 2859-2865 (Advanced Materials Research).
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Moon, JW & Kim, S 2013, Artificial neural network for the control of the openings and cooling systems of the double skin envelope buildings. in Progress in Environmental Science and Engineering. Advanced Materials Research, vol. 610-613, pp. 2859-2865, 2nd International Conference on Energy, Environment and Sustainable Development, EESD 2012, Jilin, China, 12/10/12. https://doi.org/10.4028/www.scientific.net/AMR.610-613.2859

Artificial neural network for the control of the openings and cooling systems of the double skin envelope buildings. / Moon, Jin Woo; Kim, Sooyoung.

Progress in Environmental Science and Engineering. 2013. p. 2859-2865 (Advanced Materials Research; Vol. 610-613).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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