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FEATURE SELECTION AND FEATURE SYNTHESIS METHODS FOR PREDICTIVE MODELING IN A TWINNED PHYSICAL SYSTEM
FEATURE SELECTION AND FEATURE SYNTHESIS METHODS FOR PREDICTIVE MODELING IN A TWINNED PHYSICAL SYSTEM
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机译：孪生物理系统中用于预测建模的特征选择和特征综合方法
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摘要
Systems and methods for predictive modeling of an industrial asset. In some embodiments, a database stores an electronic file containing a machine learning library and predictive modeling tools associated with the industrial asset. A computer processor accesses the machine learning library and predictive modeling tools, provides a model building framework user interface and receives a selection of a feature engineering (FE) technique, including one of evolutionary feature selection, evolutionary feature synthesis, and symbolic regression. Next, an input selection interface is provided, industrial asset input data and parameter data received, and at least one of an evolutionary feature selection process, an evolutionary feature synthesis process, and a symbolic regression process is executed. At least one of feature selection output data and feature rankings output data associated with a predictive model of the industrial asset is generated, and in some implementations an output device receives and presents that data to a user.
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