The void closure behavior in a central extra-thick plate during the gradient temperature rolling was simulated and a back propagation(BP)neural network model was established.The thermal–mechanical finite element mode...The void closure behavior in a central extra-thick plate during the gradient temperature rolling was simulated and a back propagation(BP)neural network model was established.The thermal–mechanical finite element model of the gradient temperature rolling process was first developed and validated.The prediction error of the model for the rolling force is less than 2.51%,which has provided the feasibility of imbedding a defect in it.Based on the relevant data obtained from the simulation,the BP neural network was used to establish a prediction model for the compression degree of a void defect.After statistical analysis,80%of the data had a hit rate higher than 95%,and the hit rate of all data was higher than 90%,which indicates that the BP neural network can accurately predict the compression degree.Meanwhile,the comparisons between the results with the gradient temperature rolling and uniform temperature rolling,and between the results with the single-pass rolling and multi-pass rolling were discussed,which provides a theoretical reference for developing process parameters in actual production.展开更多
目的构建早期牙髓炎患者iRoot BP Plus活髓切断术后失败的个体化预测模型。方法选取2019年1月至2021年12月于秦皇岛市海港医院进行iRoot BP Plus活髓切断术治疗的278例早期牙髓炎患者为研究对象,记录性别、年龄、穿髓孔直径等资料并进...目的构建早期牙髓炎患者iRoot BP Plus活髓切断术后失败的个体化预测模型。方法选取2019年1月至2021年12月于秦皇岛市海港医院进行iRoot BP Plus活髓切断术治疗的278例早期牙髓炎患者为研究对象,记录性别、年龄、穿髓孔直径等资料并进行统计学分析,Logistic回归分析确定危险因素,绘制列线图预测模型,进行内部验证并评估临床预测效能及实用性。结果278例早期牙髓炎iRoot BP Plus活髓切断术后失败率为10.43%。将穿髓孔直径、腐质颜色、腐质质地提取为预测因子构建列线图预测模型,列线图预测模型的校正曲线与原始曲线及理想曲线接近,C-index为0.768(95%CI:0.722~0.833),模型拟合度高;列线图预测模型的阈值>0.16,可提供临床净收益,且临床净收益均高于独立预测因子。结论以穿髓孔直径、腐质颜色、腐质质地为预测因子构建的早期牙髓炎患者iRoot BP Plus活髓切断术后失败的列线图预测模型对iRoot BP Plus活髓切断术后失败的发生具有良好的预测价值。展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.U1960105,52074187,and 52274388).
文摘The void closure behavior in a central extra-thick plate during the gradient temperature rolling was simulated and a back propagation(BP)neural network model was established.The thermal–mechanical finite element model of the gradient temperature rolling process was first developed and validated.The prediction error of the model for the rolling force is less than 2.51%,which has provided the feasibility of imbedding a defect in it.Based on the relevant data obtained from the simulation,the BP neural network was used to establish a prediction model for the compression degree of a void defect.After statistical analysis,80%of the data had a hit rate higher than 95%,and the hit rate of all data was higher than 90%,which indicates that the BP neural network can accurately predict the compression degree.Meanwhile,the comparisons between the results with the gradient temperature rolling and uniform temperature rolling,and between the results with the single-pass rolling and multi-pass rolling were discussed,which provides a theoretical reference for developing process parameters in actual production.
文摘目的构建早期牙髓炎患者iRoot BP Plus活髓切断术后失败的个体化预测模型。方法选取2019年1月至2021年12月于秦皇岛市海港医院进行iRoot BP Plus活髓切断术治疗的278例早期牙髓炎患者为研究对象,记录性别、年龄、穿髓孔直径等资料并进行统计学分析,Logistic回归分析确定危险因素,绘制列线图预测模型,进行内部验证并评估临床预测效能及实用性。结果278例早期牙髓炎iRoot BP Plus活髓切断术后失败率为10.43%。将穿髓孔直径、腐质颜色、腐质质地提取为预测因子构建列线图预测模型,列线图预测模型的校正曲线与原始曲线及理想曲线接近,C-index为0.768(95%CI:0.722~0.833),模型拟合度高;列线图预测模型的阈值>0.16,可提供临床净收益,且临床净收益均高于独立预测因子。结论以穿髓孔直径、腐质颜色、腐质质地为预测因子构建的早期牙髓炎患者iRoot BP Plus活髓切断术后失败的列线图预测模型对iRoot BP Plus活髓切断术后失败的发生具有良好的预测价值。
