02221nam 2200493 a 450 991069902770332120100607112754.0(CKB)5470000002399611(OCoLC)638967469(EXLCZ)99547000000239961120100607d2009 ua 0engurmn|||||||||txtrdacontentcrdamediacrrdacarrierForest growth and timber quality[electronic resource] crown models and simulation methods for sustainable forest management : proceedings of an international conference : Portland, OR, USA, August 7-10, 2007 /Dennis P. Dykstra and Robert A. Monserud, technical editors ; sponsored by USDA Forest Service, Pacific Northwest Research Station [and] International Union of Forest Research Organizations (IUFRO)Portland, OR. :U.S. Dept. of Agriculture, Forest Service, Pacific Northwest Research Station,[2009]1 online resource (ix, 267 pages) illustrations, mapsGeneral technical report PNW ;GTR-791"August 2009."Includes bibliographical references.Forest growth and timber quality Forest managementSimulation methodsCongressesForest productivityMathematical modelsCongressesCrowns (Botany)Mathematical modelsCongressesWoodQualityMathematical modelsCongressesSustainable forestryCongressesConference papers and proceedings.lcgftForest managementSimulation methodsForest productivityMathematical modelsCrowns (Botany)Mathematical modelsWoodQualityMathematical modelsSustainable forestryDykstra Dennis P78842Monserud Robert A1380963Pacific Northwest Research Station (Portland, Or.)International Union of Forest Research Organizations.GPOGPOBOOK9910699027703321Forest growth and timber quality3497398UNINA04347nam 22005773 450 991102021320332120250225080317.0978139427039213942703999781394270378139427037297813942703851394270380(CKB)37529492100041(MiAaPQ)EBC31907281(Au-PeEL)EBL31907281(OCoLC)1500135867(Perlego)4893422(Exl-AI)31907281(EXLCZ)993752949210004120250225d2025 uy 0engur|||||||||||txtrdacontentcrdamediacrrdacarrierEnvironmental Monitoring Using Artificial Intelligence1st ed.Newark :John Wiley & Sons, Incorporated,2025.©2025.1 online resource (423 pages)9781394270361 1394270364 Cover -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- Chapter 1 Transformative Trends in AI for Environmental Monitoring: Challenges, Applications -- 1.1 Introduction -- 1.2 Literature Verticals -- 1.3 Key Methodologies in Literature Review -- 1.4 Most Common Methods in Environmental Monitoring -- 1.5 AI Architectures for Environmental Monitoring -- 1.6 Applications of AI in Environmental Monitoring -- 1.7 Challenges and Limitations of Using AI in Environment Modeling -- 1.8 Future Directions -- 1.9 Conclusion -- Acknowledgements -- References -- Chapter 2 Fundamentals of AI and NLP in Environmental Analysis -- 2.1 Introduction -- 2.2 AI and NLP Techniques -- 2.2.1 Artificial Neural Network (ANN) -- 2.2.2 Support Vector Machine (SVM) -- 2.2.3 Linear Regression (LR) -- 2.2.4 Random Forests (RF) and Decision Trees (DT) -- 2.2.5 Adaptive Neuro-Fuzzy Inference System (ANFIS) -- 2.2.6 Batch-Normalization (BN) -- 2.2.7 Convolutional Neural Networks (CNNs) -- 2.2.8 Deep Neural Networks (DNNs) -- 2.2.9 Genetic Algorithm (GA)Generated by AI.Environmental Monitoring Using Artificial Intelligence is a vital resource for anyone looking to leverage cutting-edge technologies in artificial intelligence and sensor systems to effectively address environmental challenges, offering innovative solutions and insights essential for creating a sustainable future. Environmental Monitoring Using Artificial Intelligence provides a comprehensive exploration of the cutting-edge technologies transforming environmental monitoring. This book bridges the gap between artificial intelligence (AI), natural language processing (NLP), and sensor-based systems, highlighting their potential to revolutionize the way we address pressing environmental challenges. Each chapter presents innovative case studies, real-world applications, and the latest research on how these technologies are being utilized to monitor and manage ecosystems, water resources, air quality, and urban sustainability. From advanced sensor networks to machine learning models, this book covers a broad spectrum of topics, including smart water solutions, biodiversity conservation, waste management, and agricultural sustainability. It offers an interdisciplinary approach, making it an essential resource for environmental engineers, data scientists, researchers, and policymakers. Whether you're exploring smart city innovations, renewable energy monitoring, or AI-driven solutions for environmental protection, Environmental Monitoring Using Artificial Intelligence equips readers with the knowledge and tools to leverage technology for a sustainable future. Artificial intelligenceGenerated by AIEnvironmental monitoringGenerated by AIArtificial intelligenceEnvironmental monitoring363.7063028563Suresh A1406426Thirupathi Devi1887922Deepa N1838136Bashir Ali Kashif1762152MiAaPQMiAaPQMiAaPQBOOK9911020213203321Environmental Monitoring Using Artificial Intelligence4526040UNINA