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Creating predictive damage models by transductive transfer learning

机译:通过转导迁移学习创建预测性伤害模型

摘要

A method for creating predictive damage models includes receiving a first predictive damage model, identifying latent space between a first and a second domain asset, building a regression model from first domain asset projected source data, creating target dependent variables of a second model, applying classification or regression techniques to determine a function expressing the dependent variables, determining data points from the function to develop a second regression model, applying the second regression model to data points to predict target dependent variables, evaluating the second predictive damage model using the predicted target dependent variables, performing a sensitivity study to determine a directionality parameter of the second predictive damage model, and if the results are within an acceptable predetermined range, providing maintenance or servicing recommendations generated by the second predictive model to a user platform display, else repeating the process by rebuilding the regression model to further refine the regression model.
机译:用于创建预测性损害模型的方法包括:接收第一预测性损害模型;识别第一和第二域资产之间的潜在空间;从第一域资产投影的源数据构建回归模型;创建第二模型的目标因变量;应用分类或回归技术来确定表示因变量的函数,从函数确定数据点以开发第二回归模型,将第二回归模型应用于数据点以预测目标因变量,使用预测的目标因变量来评估第二预测损害模型变量,进行敏感性研究以确定第二个预测损害模型的方向性参数,如果结果在可接受的预定范围内,则将第二个预测模型生成的维护或服务建议提供给用户平台显示,否则重复该过程通过rebu建立回归模型以进一步完善回归模型。

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