基于大数据提升的烟叶种植环境优化下云产卷烟内在质量研究

Study on Inner Quality of Cloud Products based on Optimization of Tobacco Leaf Planting Environment based on Big Data

传统卷烟内在质量的研究存在稳定性差、速度慢、准确率低等问题,为此设定评价指标对大数据提升的烟叶种植环境优化下云产卷烟内在质量进行研究。通过可视化分析来构建三维模型,实现卷烟内在质量在大数据环境下的立体呈现,经过收集、验证和修正阶段可构成卷烟内在质量评价指标的循环过程,并对指标内容进行了设计;建立质量监控预警体系,实现卷烟生产标准的制定与修改。经过实验参数设定与实验分析,得出结论。该指标具有稳定性强、评价时间快、召回率低、准确率高的优势,适合在大数据提升的烟叶种植环境优化下云产卷烟内在质量的研究。

The problem of poor stability,slow speed and low accuracy of traditional cigarette research internal quality evaluation index,this set of data to improve the tobacco planting environment optimization under the internal quality of Yunnan cigarettes. To construct the 3 D model by visual analysis,realize the inherent quality of the cigarettes in the big data environment for three-dimensional rendering,after the collection,verification and correction stage of circulation process evaluation index cigarette internal quality,and the indexes are designed; the establishment of quality monitoring and early warning system,implementation of the formulation and revision of the cigarette production standard. After experimental parameter setting and experiment analysis,the conclusion is drawn. The index has the advantages of strong stability,fast evaluation time,low recall rate and high accuracy. It is suitable for the study of the inherent quality of tobacco cigarettes under the condition of big data promotion of tobacco planting environment.