Solution algorithm of apparent resistivity based on independent variable input mode of neural network
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Abstract:
According to the relationship between the response and the independent variables in transient electromagnetic field theory, a BP neural network with nonlinear equation model was proposed to solve the resistivity. By constructing a single-input-single-output network structure, a neural network with current normalized induced voltage at different time points as input and the apparent resistivity as the output was set up to simulate the secondary eddy current curve of the transient electromagnetic field. The accuracy of the trained network was verified by the data calculated by numerical computation, and the training accuracies and the convergence speeds of different algorithms were compared. The effectiveness of the proposed algorithm was verified by the experiments in an air-raid shelter in Chongqing University. The presented solution algorithm avoids calculation of complex electromagnetic field or numerical inverse problem, and realizes fast calculation of resistivity.
