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003			ES-MaUEC
005			20240314174526.0
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007			cr nn 008mamaa
008			230311s2023 sz | o |||| 0|eng d
020			_a9783031224560
024	7		_a10.1007/978-3-031-22456-0 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTA345 _b2023 EB
245	0	0	_aThe Power of Data : _bDriving Climate Change with Data Science and Artificial Intelligence Innovations _cedited by Aboul Ella Hassanien, Ashraf Darwish
250			_a1st ed 2023
264		1	_aCham _bSpringer Nature Switzerland _c2023
300			_a1 recurso en línea
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	0		_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.
988			_aSpringer_Computer_2023
650		7	_2embne _9152630 _aIngeniería del software
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-22456-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b01/2024 _dz _ek _zSI