Nonlinear discrete system model of tobacco supply chain information

Abstract

Abstract In order to understand the real environment and specific needs of China’s current tobacco industry, master the signal information in the tobacco supply chain, and timely discover the source of the tobacco supply chain, this paper puts forward the detection method of anti-counterfeiting at the source of the tobacco supply chain. Based on this, this article constructs a nonlinear discrete system model, which mainly studies the logistics information existing in the tobacco supply chain, utilizes the noise existing in the tobacco supply chain information obtained by EKF filtering, and combines it with Support vector machine data analysis method. The results showed that out of 450 sample tests, 0 real sample errors and 1 misuse of 49 false samples, with a total detection rate of up to 100% was achieved. The results show that the nonlinear discrete system model is better, has higher detection effect of tobacco supply source, and improves the detection accuracy.