Neural Network Solution of an Inverse Problem with Integration of Geophysical Methods on Recovered Data: Training with Noise AdditionстатьяИсследовательская статья
Дата последнего поиска статьи во внешних источниках: 22 мая 2024 г.
Аннотация:Previously, it was shown that integration (joint use of data) of several geophysical methods allows one to obtain a higher quality of the solution of the inverse problem of exploration geophysics in comparison with the individual use of each of these methods. However, there may be a situation when for some measurement points there is no data from one of the geophysical methods used. At the same time, the data spaces of different integrated geophysical methods are interconnected. Therefore, the missing data of one method can be recovered from the known data of another one by constructing a preliminary adaptive mapping of one of the spaces to another. In this study, we investigate the solution of the inverse problem with integration of geophysical methods on the recovered data obtained based on noise addition during training of the neural networks performing the mapping from the data space of the method(s) with all data present to the data space of the method with missing data.
