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- W3140364059 abstract "Geophysical inversion is a very difficult problem due to its non_linear nature. In the past decade, non_ linear inversion algorithms such as artificial neural network (NN) and genetic algorithm (GA) are increasingly used for the interpretation of geophysical data. However, until now, most of geophysical inversions using NN are limited to one_dimensional (1_D) models. As to 2_D inverse problems, NN inversion is hardly used because of a large number of parameters. In this paper, 2_D resistivity non_linear inversion is developed using the Back_Propagation (BP) neural network method. Compared to the traditional iterative inversion method through linearization, the neural network inversion is able to overcome disadvantages of the traditional inversion and obtain better results." @default.
- W3140364059 created "2021-04-13" @default.
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- W3140364059 date "2006-01-01" @default.
- W3140364059 modified "2023-09-27" @default.
- W3140364059 title "2-D resistivity inversion using the neural network method" @default.
- W3140364059 hasPublicationYear "2006" @default.
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