Quality Prediction Model Based on PCA-BP Neural Network for Tobacco Leaves Redrying Process

Abstract

Aiming to the problem that is very difficult to establish the mechanism model of quality for the process of tobacco leaves redrying, this paper proposes a quality prediction model based on principal component analysis (PCA) and improved back propagation (BP)neural network for tobacco leaves redrying process. Firstly, 12 input variables are confirmed by analyzing the factors on quality of tobacco leaves redrying process. Second, the methods of PCA is used to eliminate the correlation of original input layer data, in which 12 input variables are transformed into 6 uncorrelated indicators. Then, the quality prediction model based on improved BP neural network is established. Finally, a simulation experiment is conducted and the average prediction error is as low as 1.03%, the absolute error for forecasting is fluctuated in the range of 0.16% - 2.49%. The result indicates that the model is simpler and has higher stability for prediction, which can completely meet the actual requirements of the tobacco leaves redrying process.

Population Prediction of China Based on ARIMA-LSTM Combined Model

“…The problem of sustainable population development has been widely concerned by scholars, Zhang Tianliang (2000) used GM (1,1) grey series prediction model to predict the birth rate of China from 1994 to 2000 [1].Yin Chunhua and Chen Lei (2005) used BP neural network technology to build a population prediction model and conducted an empirical analysis [2].Rayer, S (2009) et al use of the ten-year census data of the United States from 1900 to 2000, and provided a fairly accurate prediction of the accuracy of population prediction with the prediction interval and trend extrapolation technology based on experience [3]. Mao Jiaohui (2018) predicted the birth rate of China in the next 5 years by using three prediction methods, namely multiple linear regression, exponential smoothing and ARMA model [4].Chen, LX (2022) et al used the Malthus model, unary linear regression model, Logistic model and grey prediction model to forecast the population of 210 prefecture-level cities in China [5].…”