Prediction of Tobacco Moisture Content Based on Improved Support Vector Regression Model
Shuaibo Zhao,
Nianfeng Shi,
Shibao Sun
et al.
Abstract:Drying plays a pivotal role in the production of tobacco. Unlike many other drying processes, tobacco drying exhibits significant nonlinearity and is influenced by numerous factors, rendering accurate predictions challenging. In light of these characteristics, in order to improve the accuracy of tobacco moisture content prediction, in this study, an improved support vector machine regression model was used to simulate the complex dynamic process in the tobacco drying process. Addressing the inherent limitation… Show more
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