000 04251nam a22005535i 4500
001 978-3-031-22456-0
003 DE-He213
005 20240423125406.0
007 cr nn 008mamaa
008 230311s2023 sz | s |||| 0|eng d
020 _a9783031224560
_9978-3-031-22456-0
024 7 _a10.1007/978-3-031-22456-0
_2doi
050 4 _aTA345-345.5
072 7 _aUN
_2bicssc
072 7 _aCOM018000
_2bisacsh
072 7 _aUN
_2thema
082 0 4 _a620.00285
_223
245 1 4 _aThe Power of Data: Driving Climate Change with Data Science and Artificial Intelligence Innovations
_h[electronic resource] /
_cedited by Aboul Ella Hassanien, Ashraf Darwish.
250 _a1st ed. 2023.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2023.
300 _aX, 255 p. 96 illus., 76 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Big Data,
_x2197-6511 ;
_v118
505 0 _aPart 1: Artificial Intelligence in climate change Applications -- Chapter 1. Artificial Intelligence for Predicting Floods: A Climatic Change Phenomenon -- Chapter 2. Prediction of Climate Change Impact based on Air Flight CO2 Emissions Using Machine Learning: Towards Green Air Flights -- Chapter 3. The Impact of Artificial Intelligence on Waste Management for Climate Change -- Chapter 4. A Machine Learning-based Model for Predicting Temperature under the Effects of Climate Change -- Part 2: Emerging Technologies in Industry and Energy Sector -- Chapter 5. Prediction of CO2 Emission in Cars using Machine Learning Algorithms -- Chapter 6. Climate change: the challenge of Tunisia and previsions for renewable energy production -- Chapter 7. Clean Energy Management based on Internet of Things and Sensor Networks for Climate Change Problems -- Chapter 8. Digital Twin Technology for Energy Management Systems to Tackle Climate Change Challenges -- Chapter 9. The Role of Internet of Things in Mitigating the Effect of Climate Change: Case study: An ozone prediction model -- Part 3: Emerging Climate Change Technology in Agriculture Sector -- Chapter 10. Optimized Multi-Kernel Predictive Model for the Crop Prediction with Climate Factors and Soil Properties Optimized Multi-Kernel Predictive Model for the Crop Prediction with Climate Factors and Soil Properties -- Chapter 11. An Intelligent Crop Recommendation Model for the Three Strategic Crops in Egypt based on Climate Change Data -- Chapter 12. Cost Effective Decision Support System for Smart Water Management System -- Chapter 13. The Role of Artificial Intelligence in Water Management in Agriculture for Climate Change Impacts -- Part 4: Emerging Climate Change Technologies in Healthcare Sector -- Chapter 14. The Influence of Climate Change on the Re-Emergence of Malaria Using Artificial Intelligence.
520 _aThis book discusses the advances of artificial intelligence and data sciences in climate change and provides the power of the climate data that is used as inputs to artificial intelligence systems. It is a good resource for researchers and professionals who work in the field of data sciences, artificial intelligence, and climate change applications.
650 0 _aEngineering
_xData processing.
650 0 _aComputational intelligence.
650 0 _aBig data.
650 1 4 _aData Engineering.
650 2 4 _aComputational Intelligence.
650 2 4 _aBig Data.
700 1 _aHassanien, Aboul Ella.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aDarwish, Ashraf.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031224553
776 0 8 _iPrinted edition:
_z9783031224577
776 0 8 _iPrinted edition:
_z9783031224584
830 0 _aStudies in Big Data,
_x2197-6511 ;
_v118
856 4 0 _uhttps://doi.org/10.1007/978-3-031-22456-0
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
942 _cSPRINGER
999 _c177435
_d177435