Title: Dynamic management and control of the risk of carbon dioxide content exceeding the standard in green food production base

Authors: Shengli Xu

Addresses: Department of Landscape Architecture, Xi'an International University, Xi'an 710077, China

Abstract: In order to solve the problems of low accuracy and long time consumption of the traditional monitoring methods for carbon dioxide content risk in food production areas, this paper proposes a new dynamic management and control scheme for the risk of carbon dioxide content exceeding the standard. PSO-BP neural network algorithm is used to obtain the carbon dioxide content value. The experimental results show that: the scheme can accurately monitor the change trend of carbon dioxide content, indicating the specific situation of carbon dioxide content exceeding the standard; the mean value of relative error of carbon dioxide gas content detection is less than 1.8%; and it can realise the high-efficiency and real-time control of the risk of carbon dioxide content exceeding the standard, so as to provide an effective guarantee for the safety and health of green food.

Keywords: green food; production base; carbon dioxide; content; risk control; system.

DOI: 10.1504/IJETM.2020.114132

International Journal of Environmental Technology and Management, 2020 Vol.23 No.5/6, pp.307 - 322

Received: 28 Dec 2019
Accepted: 28 Sep 2020

Published online: 09 Apr 2021 *

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