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A novel strategy for predicting the performance of open vertical refrigerated display cabinets based on the MTF model and ASVM algorithm.

Author(s) : CAO Z., GU B., MILLS G., et al.

Type of article: Article, IJR article

Summary

This paper presents a novel strategy for predicting the performance of open vertical refrigerated display cabinets which is based on a modified two-fluid (MTF) model and an adaptive support vector machine (ASVM) algorithm. A MTF model (physical model) was built for open vertical refrigerated display cabinets, and then an ASVM algorithm (machine learning algorithm) was built. To verify the quantity of air leakage from the cabinet during operation, an important performance factor of display cabinets, an MTF model was built. After the training and validation data sets were constructed from the output of the MTF model, the problem was solved using an ASVM algorithm. The defrosting water quantity and total energy consumption/total display area, achieved from the experiments by using the predicted combination of the controlled parameters, were found to be reduced by 39.2 and 19.3%, respectively, from the experimental results of the original display cabinet.

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Pages: pp. 1413-1424

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Details

  • Original title: A novel strategy for predicting the performance of open vertical refrigerated display cabinets based on the MTF model and ASVM algorithm.
  • Record ID : 2010-1169
  • Languages: English
  • Source: International Journal of Refrigeration - Revue Internationale du Froid - vol. 33 - n. 7
  • Publication date: 2010/11

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