On March 24, 2021, the intelligent computing team invited Professor Zhongke Gao from Tianjin University to give a report on Multi-source information fussion based on complex network and deep learling and its applications in oil well parameter measurement.
In this report, Professor Zhongke Gao first introduced the relevant background knowledge of complex network time series analysis and multi-source information fussion, which can be used to solve the problems related to multi-phase flow sensor multi-source information fusion and parameter measurement. Taking petroleum engineering as an example, the application of this method in oil well parameters is introduced in detail. Finally, he introduced the multi-channel information fusion an application of electroencephalogram (EEG), which attracted the interests of taechers and students, and launched in-depth discussions.
[Editor:Ziheng Rong]
