Remote Sensing, Artificial Intelligence and Deep Learning in Hydraulic Structure Safety Monitoring (Hardcover)
Language: English
Published by Mdpi AG, 2025
- Hardcover
- New

Seller: CitiRetail, Stevenage, United KingdomCitiRetail
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Condition: New
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Hardcover. With the gradual transformation of hydraulic engineering from digitization and intelligence to WISDOM, remote sensing technology, artificial intelligence and deep learning methods have been widely used for automatic perception, processing, storage and analysis of hydraulic structure engineering monitoring data. The advent of remote sensing technologies such as three-dimensional tilt photography offers the opportunity to build an integrated hydraulic engineering monitoring and acquisition system that is capable of capturing all the details of hydraulic engineering. With the introduction of artificial intelligence and deep learning methods, hydraulic engineering information has been analyzed and exploited efficiently. Combined with traditional hydraulic structure behavior analysis methods, such as geotechnical testing and numerical simulation, artificial intelligence and deep learning methods can help solve more complex hydraulic engineering problems by providing more accurate and professional intelligent analysis and ubiquitous hydraulic engineering services of great theoretical importance and application value in order to achieve the general improvement of the safety monitoring of hydraulic structures. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…
Seller Inventory # 9783725854455
- Title
- Remote Sensing, Artificial Intelligence and Deep Learning in Hydraulic Structure Safety Monitoring (Hardcover)
- Author
- Chenfei Shao
- Publisher
- Mdpi AG
- Publication year
- 2025
- Condition
- new
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 3725854459
- ISBN 13
- 9783725854455
With the gradual transformation of hydraulic engineering from digitization and intelligence to WISDOM, remote sensing technology, artificial intelligence and deep learning methods have been widely used for automatic perception, processing, storage and analysis of hydraulic structure engineering monitoring data. The advent of remote sensing technologies such as three-dimensional tilt photography offers the opportunity to build an integrated hydraulic engineering monitoring and acquisition system that is capable of capturing all the details of hydraulic engineering. With the introduction of artificial intelligence and deep learning methods, hydraulic engineering information has been analyzed and exploited efficiently. Combined with traditional hydraulic structure behavior analysis methods, such as geotechnical testing and numerical simulation, artificial intelligence and deep learning methods can help solve more complex hydraulic engineering problems by providing more accurate and professional intelligent analysis and ubiquitous hydraulic engineering services of great theoretical importance and application value in order to achieve the general improvement of the safety monitoring of hydraulic structures.
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CitiRetail
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