Neural network forecasting of terms of refrigerating storage of vegetative raw materials in modules with the modified atmosphere

Authors

  • В.Н. Радионенко Одесская государствення академия холода, Кафедра холодильной и торговой техники Донецкий национальный университет экономики и торговли имени Михаила Туган-Барановского, Ukraine

DOI:

https://doi.org/10.15587/1729-4061.2010.2702

Keywords:

refrigeration storage, artificial neural networks, shelf life forecast

Abstract

Modified atmosphere compact modules have been considered as a refrigeration technology tool for phytogenic product storage in the domestic refrigerators. Experimental data on kinetics of deterioration for apples were used to correlate the shelf life and different technological factors via artificial neural networks.

Author Biography

В.Н. Радионенко, Одесская государствення академия холода, Кафедра холодильной и торговой техники Донецкий национальный университет экономики и торговли имени Михаила Туган-Барановского

Аспирант,

Старший преподаватель

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Published

2010-04-06

How to Cite

Радионенко, В. (2010). Neural network forecasting of terms of refrigerating storage of vegetative raw materials in modules with the modified atmosphere. Eastern-European Journal of Enterprise Technologies, 2(7(44), 48–52. https://doi.org/10.15587/1729-4061.2010.2702

Issue

Vol. 2 No. 7(44) (2010): Energy saving technologies and equipment

Section

Energy-saving technologies and equipment

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Copyright (c) 2014 В.Н. Радионенко

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