制丝工艺流程的智能化平台系统设计

Design of intelligent platform system for silk making process

在烟草制丝工艺流程中,TB1水流量输入预测值、回潮后水分、烘丝机出口含水率等的预测是非常关键的一步。文章利用历史产生的数据,结合支持向量机、线性回归、随机森林等传统的机器学习方法进行数据的分析整合,从而建立在制丝工艺流程中能够稳定预测模型的智能化平台,通过该平台能够对技术参数进行精准预测,而且便于实时预测。

In the process of tobacco processing, the prediction of TB1 water flow input, moisture content after moisture regain, and moisture content at the outlet of silk dryer is a very important step. In this paper, the historical data and traditional machine learning methods such as support vector machine, linear regression and random forest are used to analyze and integrate the data, so as to establish a stable prediction model in the process of tobacco processing intelligent platform, through which the technical parameters can be accurately predicted, and it is convenient for real-time prediction.