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230501s2023 ne o 000 0 eng d |
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|a YDX
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|a 020870833
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|a 550.285/63
|2 23/eng/20230508
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| 245 |
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|a Artificial intelligence in earth science :
|b best practices and fundamental challenges /
|c edited by Ziheng Sun, Nicoleta Cristea, Pablo Rivas.
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| 260 |
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|a Amsterdam :
|b Elsevier,
|c 2023.
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| 300 |
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|a 1 online resource
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| 336 |
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|a text
|2 rdacontent
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|a computer
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|a online resource
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|a <B>Part I: Fundamentals of Earth AI<br></b>1. Basic Concepts of Earth AI<br>2. Introductory AI Algorithms<br>3. AI Infrastructure -- hardware and software for developing Earth AI<br><br><b>Part II. Existing Best Practices</b><br>4. AI for Earthquake Hidden Signal Detection<br>5. AI for Dust Storm Detection<br>6. AI for Snow Monitoring<br>7. AI for Volcano Pre-warning and Prediction<br>8. AI for Landslide Damage Assessment<br>9. AI for Hurricane Prediction<br>10. AI for Precipitation Prediction<br>11. AI for Drought Monitoring<br>12. AI for Wildfire Detection<br>13. AI for Air Quality Prediction<br>14. AI for Agricultural Irrigation Decision Making<br>15. AI for Land Cover Land Use Classification<br>16. AI for Ocean mesoscale eddies detection<br><br><b>Part III Fundamental Challenges for AI in Earth Sciences</b><br>17. AI Model Selection and Tuning<br>18. Training Data Preparation<br>19. Explainable AI<br>20. AI Generalization <br>21. AI Integration with Physics-based Models <br>22. AI Provenance (Replicability & Reproducibility)<br>23. AI Ethics
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| 650 |
|
0 |
|a Artificial intelligence
|x Geophysical applications.
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| 650 |
|
0 |
|a Earth sciences
|x Data processing.
|
| 650 |
|
6 |
|a Intelligence artificielle
|x Applications g�eophysiques.
|0 (CaQQLa)201-0382098
|
| 650 |
|
7 |
|a Artificial intelligence
|x Geophysical applications
|2 fast
|0 (OCoLC)fst00817259
|
| 650 |
|
7 |
|a Earth sciences
|x Data processing
|2 fast
|0 (OCoLC)fst00900738
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| 700 |
1 |
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|a Sun, Ziheng,
|e editor.
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| 700 |
1 |
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|a Cristea, Nicoleta,
|e editor.
|1 https://isni.org/isni/0000000053481232
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| 700 |
1 |
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|a Rivas Perea, Pablo,
|d 1980-
|e editor.
|
| 776 |
0 |
8 |
|i Print version:
|z 0323917372
|z 9780323917377
|w (OCoLC)1331704030
|
| 856 |
4 |
0 |
|u https://sciencedirect.uam.elogim.com/science/book/9780323917377
|z Texto completo
|
