Landslide susceptibility evaluation method and device, equipment and storage medium
A technology of easy-to-fire and predictive methods, applied in the field of deep learning, can solve problems such as heavy workload and no consideration of spatial information between regions
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Embodiment 1
[0026] figure 1 It is a flow chart of the landslide susceptibility prediction method provided in Embodiment 1 of the present invention. This embodiment can be applied to the situation of predicting the landslide susceptibility in an area based on multiple influencing factors in an area. The method can Executed by a landslide susceptibility device, the landslide susceptibility device may be implemented by software and / or hardware, and the landslide susceptibility device may be configured on a computing device, specifically including the following steps:
[0027] S110. Obtain at least one impact factor layer of the landslide data of the landslide area to be predicted, wherein each of the impact factor layers includes a classification result of the impact factor corresponding to the landslide area to be predicted.
[0028] Exemplarily, the landslide area to be predicted may be an area including at least one landslide site that needs to be predicted for landslide susceptibility, a...
Embodiment 2
[0055] image 3 It is a flow chart of the method for predicting landslide susceptibility provided by Embodiment 2 of the present invention. The embodiment of the present invention can be combined with the various alternatives in the foregoing embodiments. In the embodiment of the present invention, optionally, before the acquisition of at least one impact factor layer of landslide data in the landslide area to be predicted, the method further includes: based on the at least one historical landslide data, determining each historical landslide At least one influence factor layer of the data, and the landslide position information in each described historical landslide data; Based on the at least one influence factor layer, determine the training sample of the neural network model; Based on the training sample and the landslide position information to train the landslide susceptibility prediction model.
[0056] like image 3 As shown, the method of the embodiment of the presen...
Embodiment 3
[0080] Figure 5 It is a flow chart of the method for predicting landslide susceptibility provided by Embodiment 3 of the present invention. The embodiment of the present invention can be combined with various alternatives in the foregoing embodiments. In the embodiment of the present invention, optionally, after based on the at least one historical landslide data, the method further includes: performing enhancement processing on the at least one historical landslide data to obtain target historical landslide data; wherein, the The ways of enhancing processing include: at least one of scale transformation, scaling transformation, flip transformation, translation transformation, affine transformation, noise perturbation and black block occlusion. And, preprocessing the at least one historical landslide data; wherein, the preprocessing includes at least one of the following: transforming the at least one historical landslide data into the same coordinate system, performing a pro...
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Abstract
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Application Information
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