Remote Sensing, Artificial Intelligence and Deep Learning in Hydraulic Structure Safety Monitoring
Mitwirkende(r): Resource type: Ressourcentyp: Buch (Online)Buch (Online)Sprache: Englisch Verlag: CH : MDPI - Multidisciplinary Digital Publishing Institute, 2025Beschreibung: 1 Online-Ressource (1 electronic resource 306 p.)ISBN:- 9783725854455
- 9783725854462
- Technology, Engineering, Agriculture, Industrial processes
- Technology: general issues
- History of engineering and technology
- Artificial dam
- Artificial intelligence
- BP neural network
- BiLSTM
- Cloud model
- Coal mine
- Coal pillar dam
- Cofferdam
- Concrete dam
- Concrete face rockfill dam
- Core wall rockfill dam
- Crack detection
- Dam monitoring data
- Dam safety
- Data processing
- Deformation
- Deformation prediction
- Deformation prediction model
- Double-row sheet pile
- Environmental change
- FCM algorithm
- Factor mining
- Feature engineering
- Feature fusion
- Finite element method
- Frazil ice floe
- Frazil ice jam
- Global sensitivity analysis
- Gross errors
- Göksu Stream
- Harris hawks optimization
- High concrete dam
- Hydraulic structure
- Ice jam
- Ice morphometry
- In situ observation data
- Individual effect values
- Information entropy
- Integrated numerical analysis
- Knowledge distillation
- LOF algorithm
- Long short-term memory
- MHHO
- Machine learning
- Maximum entropy principle
- Nonuniform deformation
- OPTICS algorithm
- Performance indicators
- Phreatic line
- Prediction model
- Pumped storage power station
- Random coefficient model
- Remote sensing
- Residual neural network
- Seagull optimization algo
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eng