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City water logging analysis method based on transfer learning

A technology of urban waterlogging and transfer learning, applied in text database clustering/classification, instrumentation, electrical digital data processing, etc., can solve the problems of lack of sample data and difficulty in model training, and achieve low cost and high scalability Effect

Inactive Publication Date: 2017-08-08
ZHEJIANG UNIV
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AI Technical Summary

Problems solved by technology

However, for some small cities, due to lack of data and sparse sample data, the training of the model is relatively difficult

Method used

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  • City water logging analysis method based on transfer learning
  • City water logging analysis method based on transfer learning
  • City water logging analysis method based on transfer learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0038] Select Beijing, Shanghai, Guangzhou, Wuhan, and Shenzhen as the source cities, and Hangzhou as the target city for waterlogging analysis. According to the size and population distribution of Hangzhou City, Hangzhou City is divided into multiple rectangular areas with a width of 500 meters and a length of 600 meters, and the central longitude and latitude coordinates of a series of rectangular areas are obtained. After obtaining the central coordinate point, call the API to obtain the corresponding area. social media data and physical sensor data.

[0039] Then construct the social media features and physical sensor features respectively, and use the multi-view algorithm to perform feature fusion on the features of each region and each time period. The analysis shows that the characteristics of these cities and the data characteristics of Hangzhou obey different distributions, that is, this The relative entropy of the five cities and Hangzhou features is greater than the t...

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Abstract

The invention discloses a city water logging analysis method based on transfer learning. The method comprises steps as follows: firstly, an area is divided according to characteristics of a city; then, features are constructed by use of social media in each area and sensor data, and the features are fused to the best by use of multi-view learning; finally, big city water logging knowledge with the rich data volume is transferred to smaller cities through transfer learning, and a water logging severity degree model for the smaller cities is trained. Different view data are fused through multi-view learning, data from other sources can be effectively extended, and meanwhile, on the basis of a transfer learning technology, the method can also have a better effect for small cities with smaller samples.

Description

technical field [0001] The invention belongs to the field of data mining and urban computing, and in particular relates to an urban waterlogging analysis method based on migration learning. Background technique [0002] With the gradual expansion of the city scale, urban waterlogging caused by strong convective weather and other factors has become one of the most serious hidden dangers in China in recent years. According to statistics, in the past two years, more than 100 cities have experienced serious waterlogging. The waterlogging that occurred in Beijing and Wuhan even caused serious casualties, traffic paralysis, and severe economic losses. The current urban flood detection mostly uses sensors such as water level gauges and cameras, which have a small coverage and high cost. [0003] With the development of social media and mobile Internet, when an emergency occurs, relevant texts sent by users, such as urban waterlogging and other information, can effectively describ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06F17/27G06Q50/26
CPCG06Q50/265G06F16/35G06F40/284
Inventor 陈华钧张宁豫陈曦吴朝晖
Owner ZHEJIANG UNIV
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