Summary
The authors present the practicability of applying artificial neural network to forecast performance of ground-source heat pump units. They establish the forecasting model and simulates and forecasts the operating performance of a unit. The deviation coefficient between the simulating value and experimental value is less than 2.63%.
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Details
- Original title: [In Chinese. / En chinois.]
- Record ID : 2008-1380
- Languages: Chinese
- Source: HV & AC - vol. 37 - n. 205
- Publication date: 2007/11
Links
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Indexing
- Themes: Heat pumps techniques
- Keywords: Winter; Ground-water; Artificial neural network; Simulation; Heat pump; Performance; Modelling
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Modelling a ground-coupled heat pump system usi...
- Author(s) : ESEN H., INALLI M., SENGUR A., et al.
- Date : 2008/01
- Languages : English
- Source: International Journal of Refrigeration - Revue Internationale du Froid - vol. 31 - n. 1
- Formats : PDF
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Forecasting of a ground-coupled heat pump perfo...
- Author(s) : ESEN H., INALLI M., SENGUR A., et al.
- Date : 2008/04
- Languages : English
- Source: International Journal of thermal Sciences - vol. 47 - n. 4
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Gradual fault early stage diagnosis for air sou...
- Author(s) : SUN Z., JIN H., GU J., et al.
- Date : 2019/11
- Languages : English
- Source: International Journal of Refrigeration - Revue Internationale du Froid - vol. 107
- Formats : PDF
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A novel deep reinforcement learning based metho...
- Author(s) : LIU T., XU C., GUO Y., et al.
- Date : 2019/11
- Languages : English
- Source: International Journal of Refrigeration - Revue Internationale du Froid - vol. 107
- Formats : PDF
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Artificial intelligence models for refrigeratio...
- Author(s) : ADELEKAN D. S., OHUNAKIN O. S., PAUL B. S.
- Date : 2022/11
- Languages : English
- Source: Energy Reports - vol. 8
- Formats : PDF
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