Adnène Arbi is a distinguished academic affiliated with the University of Carthage in Tunisia, where he has contributed significantly to the fields of mathematics and engineering. His tenure at the university spans over a decade, during which he has held various positions, including roles at the Ecole Polytechnique de Tunisie and the National Institute of Applied Sciences and Technology. His research interests primarily focus on neural networks, dynamical systems, and mathematical modeling, with a particular emphasis on the stability and controllability of complex systems. Arbi's recent publications reflect his commitment to advancing knowledge in applied mathematics, particularly through innovative approaches such as wavelet neural networks and the dynamics of nonlinear systems. His work has been published in reputable journals, contributing to the understanding of mathematical phenomena in both theoretical and practical contexts.
Dr. Walid Ben Ameur earned his PhD from the University of Carthage. He currently serves as a teacher-researcher at the Department of Life Sciences, Faculty of Sciences of Gabès, Tunisia, and is a member of the Laboratory of Ecology of Terrestrial Fauna at the University of Gabès, Tunisia. Walid Ben Ameur has authored more than 20 peer-reviewed scientific papers published in international journals. His work has made useful contributions to the field of environmental chemistry, with a particular focus on persistent organic pollutants. He has developed analytical techniques for assessing emerging pollutants and evaluating their effects on both the environment and human health. His research spans a diverse range of samples, including those from environmental, biological, human, and food sources. Dr. Ben Ameur has mentored three Master's students and regularly serves as a reviewer for respected journals such as Science of the Total Environment, Chemosphere, Environmental Science and Pollution Research, Marine Pollution Bulletin, Environmental Pollution, Ecotoxicology and Environmental Safety, and Chemistry Africa.
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Paperback. Etat : new. Paperback. Invasive species represent a major threat to biodiversity, ecosystems, and global economies, contributing to habitat destruction, species loss, and the disruption of ecological functions. Conventional methods for managing these species often prove inadequate due to limitations in resources, inefficiencies in monitoring large areas, delayed responses, and challenges in forecasting their spread. With increasing pressure from factors like climate change and human activities, there is a pressing need for more effective, scalable, and adaptable approaches. Artificial intelligence applications in conservation efforts may transform the management of invasive species and strengthen biodiversity conservation efforts, enhancing early detection, tracking, and control. Harnessing AI for Invasive Species Management and Biodiversity Conservation examines the challenges of integrating AI into ecological management, including concerns about data privacy, algorithm transparency, and the need for rigorous validation processes. It highlights how AI can serve as a powerful complement to traditional conservation strategies, providing innovative and sustainable solutions to combat the growing issue of invasive species. This book covers topics such as climate change, ecology, and sustainable development, and is a useful resource for business owners, engineers, policymakers, biologists, academicians, researchers, and environmental scientists. "This book aims to explore theoretical frameworks, technical advancements, and interdisciplinary approaches that integrate ecological science with cutting-edge AI technologies"-- Provided by publisher. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9798337346175
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Paperback. Etat : new. Paperback. Invasive species represent a major threat to biodiversity, ecosystems, and global economies, contributing to habitat destruction, species loss, and the disruption of ecological functions. Conventional methods for managing these species often prove inadequate due to limitations in resources, inefficiencies in monitoring large areas, delayed responses, and challenges in forecasting their spread. With increasing pressure from factors like climate change and human activities, there is a pressing need for more effective, scalable, and adaptable approaches. Artificial intelligence applications in conservation efforts may transform the management of invasive species and strengthen biodiversity conservation efforts, enhancing early detection, tracking, and control. Harnessing AI for Invasive Species Management and Biodiversity Conservation examines the challenges of integrating AI into ecological management, including concerns about data privacy, algorithm transparency, and the need for rigorous validation processes. It highlights how AI can serve as a powerful complement to traditional conservation strategies, providing innovative and sustainable solutions to combat the growing issue of invasive species. This book covers topics such as climate change, ecology, and sustainable development, and is a useful resource for business owners, engineers, policymakers, biologists, academicians, researchers, and environmental scientists. "This book aims to explore theoretical frameworks, technical advancements, and interdisciplinary approaches that integrate ecological science with cutting-edge AI technologies"-- Provided by publisher. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9798337346175
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Paperback. Etat : new. Paperback. Invasive species represent a major threat to biodiversity, ecosystems, and global economies, contributing to habitat destruction, species loss, and the disruption of ecological functions. Conventional methods for managing these species often prove inadequate due to limitations in resources, inefficiencies in monitoring large areas, delayed responses, and challenges in forecasting their spread. With increasing pressure from factors like climate change and human activities, there is a pressing need for more effective, scalable, and adaptable approaches. Artificial intelligence applications in conservation efforts may transform the management of invasive species and strengthen biodiversity conservation efforts, enhancing early detection, tracking, and control. Harnessing AI for Invasive Species Management and Biodiversity Conservation examines the challenges of integrating AI into ecological management, including concerns about data privacy, algorithm transparency, and the need for rigorous validation processes. It highlights how AI can serve as a powerful complement to traditional conservation strategies, providing innovative and sustainable solutions to combat the growing issue of invasive species. This book covers topics such as climate change, ecology, and sustainable development, and is a useful resource for business owners, engineers, policymakers, biologists, academicians, researchers, and environmental scientists. "This book aims to explore theoretical frameworks, technical advancements, and interdisciplinary approaches that integrate ecological science with cutting-edge AI technologies"-- Provided by publisher. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. N° de réf. du vendeur 9798337346175
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Taschenbuch. Etat : Neu. Harnessing AI for Invasive Species Management and Biodiversity Conservation | Adnène Arbi (u. a.) | Taschenbuch | Englisch | 2026 | IGI GLOBAL SCIENTIFIC PUBLISHING | EAN 9798337346175 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. N° de réf. du vendeur 134458231
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