Zhejiang University

Huifang Zhou

Shuyou Zhang

Yang Wang

Zili Wang

Lemiao Qiu

Disclosed is a customized product performance prediction method based on heterogeneous data difference compensation fusion. The method includes: on the basis of a depth auto-encoder, a neighborhood association method and a similarity difference compensation method, performing difference compensation correction on a calculation simulation data set by using a historical actual measurement data set; and training a BP neural network model by using the calculation simulation data set after the difference compensation correction to serve as a performance prediction method of a customized product. According to the method of the present application, by combining the depth auto-encoder, and by utilizing the neighborhood association method and the similarity difference compensation method, low-fidelity calculation simulation data is associated with high-fidelity historical actual measurement data, such that the difference compensation correction of the low-fidelity calculation simulation data is realized by using the high-fidelity historical actual measurement data.

Growing community of inventors

Hangzhou, China

Huifang Zhou