Artificial Intelligence Methods in the Environmental Sciences
How can environmental scientists and engineers use the increasing amount of available data to enhance our understanding of planet Earth, its systems and processes? This book describes various potential approaches based on artificial intelligence techniques, including: -neural networks -decision tree...
| Συγγραφή απο Οργανισμό/Αρχή: | |
|---|---|
| Άλλοι συγγραφείς: | , , |
| Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
| Γλώσσα: | English |
| Έκδοση: |
Dordrecht :
Springer Netherlands,
2009.
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| Θέματα: | |
| Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- to AI for Environmental Science
- Environmental Science Models and Artificial Intelligence
- Basic Statistics and Basic AI: Neural Networks
- Performance Measures and Uncertainty
- Decision Trees
- to Genetic Algorithms
- to Fuzzy Logic
- Missing Data Imputation Through Machine Learning Algorithms
- Applications of AI in Environmental Science
- Nonlinear Principal Component Analysis
- Neural Network Applications to Solve Forward and Inverse Problems in Atmospheric and Oceanic Satellite Remote Sensing
- Implementing a Neural Network Emulation of a Satellite Retrieval Algorithm
- Neural Network Applications to Developing Hybrid Atmospheric and Oceanic Numerical Models
- Neural Network Modeling in Climate Change Studies
- Neural Networks for Characterization and Forecasting in the Boundary Layer via Radon Data
- Addressing Air Quality Problems with Genetic Algorithms: A Detailed Analysis of Source Characterization
- Reinforcement Learning of Optimal Controls
- Automated Analysis of Spatial Grids
- Fuzzy Logic Applications
- Environmental Optimization: Applications of Genetic Algorithms
- Machine Learning Applications in Habitat Suitability Modeling.
