Small-sample large-scale regional landslide susceptibility evaluation method based on transfer learning
The invention discloses a small-sample large-scale regional landslide susceptibility evaluation method based on transfer learning, and the method comprises the following steps: S1, obtaining a historical landslide record of a research region, obtaining influence factor multi-source data, and unifyin...
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| creator | ZHANG WENGANG WANG YANKUN LI JIAYI WANG YUNHAO WANG LUQI JIANG CHENG ZHU CHUN LIU SONGLIN XU JIN LIU JING HAO XINGENG KANG YANFEI LI TAO |
| description | The invention discloses a small-sample large-scale regional landslide susceptibility evaluation method based on transfer learning, and the method comprises the following steps: S1, obtaining a historical landslide record of a research region, obtaining influence factor multi-source data, and unifying the spatial resolution, a projection coordinate system and a geographic coordinate system of the multi-source data; s2, acquiring an influence factor layer related to a landslide, extracting landslide influence factor information from the multi-source data through a GIS platform, and establishing a landslide susceptibility influence factor system; s3, on the basis of the landslide sample data set of the source domain, constructing a deep learning model, and pre-training the model; according to the method, the problem that the landslide susceptibility is predicted by using a machine learning method under the condition that the landslide sample size of a large-scale region is insufficient is solved; the investment |
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s2, acquiring an influence factor layer related to a landslide, extracting landslide influence factor information from the multi-source data through a GIS platform, and establishing a landslide susceptibility influence factor system; s3, on the basis of the landslide sample data set of the source domain, constructing a deep learning model, and pre-training the model; according to the method, the problem that the landslide susceptibility is predicted by using a machine learning method under the condition that the landslide sample size of a large-scale region is insufficient is solved; the investment</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2024</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNijEKwkAQRdNYiHqH8QABYxBtJShWNtqHSfZnXZhslp2N4O3dwgNYvf8-b1nYx8gipfIYBCQcLUrtOe8I6ybPkk9vVJwB6aw9QnKdE5c-hDfLzClXNCK9JkMdKwxlT5G9Dogk4Oidt-tiMbAoNj-uiu318mxuJcLUQgP38Ehtc6-q02G_2x_rc_1P8wUgUkC4</recordid><startdate>20240820</startdate><enddate>20240820</enddate><creator>ZHANG WENGANG</creator><creator>WANG YANKUN</creator><creator>LI JIAYI</creator><creator>WANG YUNHAO</creator><creator>WANG LUQI</creator><creator>JIANG CHENG</creator><creator>ZHU CHUN</creator><creator>LIU SONGLIN</creator><creator>XU JIN</creator><creator>LIU JING</creator><creator>HAO XINGENG</creator><creator>KANG YANFEI</creator><creator>LI TAO</creator><scope>EVB</scope></search><sort><creationdate>20240820</creationdate><title>Small-sample large-scale regional landslide susceptibility evaluation method based on transfer learning</title><author>ZHANG WENGANG ; 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s2, acquiring an influence factor layer related to a landslide, extracting landslide influence factor information from the multi-source data through a GIS platform, and establishing a landslide susceptibility influence factor system; s3, on the basis of the landslide sample data set of the source domain, constructing a deep learning model, and pre-training the model; according to the method, the problem that the landslide susceptibility is predicted by using a machine learning method under the condition that the landslide sample size of a large-scale region is insufficient is solved; the investment</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PHYSICS |
| title | Small-sample large-scale regional landslide susceptibility evaluation method based on transfer learning |
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