LEADER 01164nam0 22002891i 450 001 RML0307017 005 20231121125748.0 100 $a20121121d2007 ||||0itac50 ba 101 | $aeng 102 $aus 181 1$6z01$ai $bxxxe 182 1$6z01$an 200 1 $aInstantaneous power theory and applications to power conditioning$fHirofumi Akagi, Edson Hirokazu Watanabe, Mauricio Aredes 210 $aHoboken $cJohn Wiley & Sons - Piscataway $cIEEE Press $d2007 215 $aXIV, 380 p.$d24 cm 676 $a621.3815324$9$v21 700 1$aAkagi$b, Hirofumi$3RMLV197904$0521957 701 1$aAredes$b, Mauricio$3RMLV197902$0521959 701 1$aWatanabe$b, Edson Hirokazu$3RMLV197903$0521958 801 3$aIT$bIT-01$c20121121 850 $aIT-FR0099 899 $aBiblioteca Area Ingegneristica$bFR0099 912 $aRML0307017 950 0$aBiblioteca Area Ingegneristica$d 54DII 621.381 AKA$e 54VM 0000770165 VM barcode:BAIN004207. - Inventario:5847DVM$fA $h20081103$i20121204 977 $a 54 996 $aInstantaneous power theory and applications to power conditioning$9835199 997 $aUNICAS LEADER 05013nam 22007095 450 001 9910861089503321 005 20250807145543.0 010 $a981-9716-85-3 024 7 $a10.1007/978-981-97-1685-2 035 $a(MiAaPQ)EBC31347249 035 $a(Au-PeEL)EBL31347249 035 $a(CKB)32136561900041 035 $a(DE-He213)978-981-97-1685-2 035 $a(EXLCZ)9932136561900041 100 $a20240519d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aBig Data, Artificial Intelligence, and Data Analytics in Climate Change Research $eFor Sustainable Development Goals /$fedited by Gaurav Tripathi, Achala Shakya, Shruti Kanga, Suraj Kumar Singh, Praveen Kumar Rai 205 $a1st ed. 2024. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2024. 215 $a1 online resource (339 pages) 225 1 $aAdvances in Geographical and Environmental Sciences,$x2198-3550 311 08$a981-9716-84-5 327 $aExperimental analysis of Precipitation Forecasting Using Machine Learning and Distributed Machine Learning Approach -- Analysis of Inherent Memory in Hydroclimatic Time Series: Implications for Statistical Tests and Long-Term Data Generation -- Intelligent Solutions for Flood Management: Integrating Artificial Intelligence and Machine Learning -- Artificial Intelligence and Machine Learning based building solutions: Pathways to ensure occupants comfort and energy efficiency with climate change -- Deep Learning models for fine-scale Climate Change prediction: enhancing spatial and temporal resolution using AI -- Exploring streamflow variation in the Subarnarekha River basin, Jharkhand, India -- Geoinformatics Based Land Degradation Susceptibility Analysis and Sustainability of Palghar Sea Coastal Areas -- Climate Change and Maritime Security in the Indo-Pacific Region: A Strategic Approach -- Climate Change and Renewable Energy -- Sustainable Development Goals and Indian Himalayan Region -- Climate Change and Energy Aspects -- Mustard Yield forecast using Radiation use efficiency method -- Public Private Partnership for Climate Change Research -- Groundwater and Sustainable Development Goals: Water Table Characteristics in Varanasi City -- Approach of Hydro geomorphological Mapping for Groundwater Resource Management in Mirzapur District, Uttar Pradesh -- Soil erosion assessment of Rohru C.D. Block of Himachal Pradesh using Geospatial Tools -- Impact of Sarangkheda Dam construction on the downstream reach of Tapi River, Nandurbar District, Maharashtra. 330 $aThis book explores the potential of big data, artificial intelligence (AI), and data analytics to address climate change and achieve the Sustainable Development Goals (SDGs). Furthermore, the book covers a wide range of related topics, including climate change data sources, big data analytics techniques, remote sensing, renewable energy, open data, public?private partnerships, ethical and legal issues, and case studies of successful applications. The book also discusses the challenges and opportunities presented by these technologies and provides insights into future research directions. In order to address climate change and achieve the SDGs, it is crucial to understand the complex interplay between climate and environmental factors. The use of big data, AI, and data analytics can play a vital role in this effort by providing the means to collect, process, and analyze vast amounts of environmental data. This book is an essential resource for researchers, policymakers, and practitioners interested in leveraging these technologies to tackle the pressing challenge of climate change and achieve the SDGs. 410 0$aAdvances in Geographical and Environmental Sciences,$x2198-3550 606 $aClimatology 606 $aBig data 606 $aArtificial intelligence 606 $aQuantitative research 606 $aSustainability 606 $aClimate Sciences 606 $aBig Data 606 $aArtificial Intelligence 606 $aData Analysis and Big Data 606 $aSustainability 615 0$aClimatology. 615 0$aBig data. 615 0$aArtificial intelligence. 615 0$aQuantitative research. 615 0$aSustainability. 615 14$aClimate Sciences. 615 24$aBig Data. 615 24$aArtificial Intelligence. 615 24$aData Analysis and Big Data. 615 24$aSustainability. 676 $a551.6 700 $aTripathi$b Gaurav$01739291 701 $aShakya$b Achala$01739292 701 $aKanga$b Shruti$01737514 701 $aSingh$b Suraj Kumar$01737513 701 $aRai$b Praveen Kumar$0929099 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910861089503321 996 $aBig Data, Artificial Intelligence, and Data Analytics in Climate Change Research$94163268 997 $aUNINA