制备硒化锌陶瓷预测最佳烧结温度数据

将采集到的数据使用一元线性回归模型用来预测制备陶瓷过程中的最佳烧结温度。该模型在泥浆比重、泥浆水分、稠化性、回坯泥比重、釉浆细度等数据为固定量条件下，通过该预测模型来预测最佳坯体收缩率时的烧结温度，从而能够为制备陶瓷预测出最佳的烧结温度，为广大的陶瓷生产企业提高了产品质量和生产效率提供技术支持。将采集到的数据使用一元线性回归模型用来预测制备陶瓷的最佳烧结温度。该模型在泥浆比重、泥浆水分、稠化性、回坯泥比重、釉浆细度等数据为固定量条件下，烧结温度与坯体收缩率构成一元函数关系（y（坯体收缩率）=F(烧结温度)），通过该函数公式来反推根据因变量变化的变化，在最佳坯体收缩率时根据极大似然法取概率分布最大的烧结温度的取值，从而能够为制备陶瓷预测出最佳的烧结温度。

Collected data is utilized to construct a simple linear regression model for predicting the optimal sintering temperature during ceramic fabrication. With fixed variables including slurry specific gravity, slurry moisture content, thickening property, returned green body specific gravity, and glaze slip fineness, the model establishes a univariate functional relationship between sintering temperature and green body shrinkage rate, expressed as y (green body shrinkage rate) = F(sintering temperature). Based on this functional formula, inverse derivation of variations driven by the dependent variable is conducted. When the green body shrinkage rate attains its optimal value, the maximum likelihood estimation (MLE) is applied to select the sintering temperature value corresponding to the maximum probability distribution, thus enabling accurate prediction of the optimal sintering temperature for ceramic preparation. This provides technical support for a wide range of ceramic production enterprises to improve product quality and production efficiency.

搜集汇总

数据集介绍

特点

该数据集用于预测硒化锌陶瓷制备过程中的最佳烧结温度，包含12833条数据，每月更新。数据集通过一元线性回归模型，基于泥浆比重、水分等固定参数，预测最佳烧结温度，帮助陶瓷生产企业优化生产工艺。