Diego Alberto Oliva Navarro – författare

Harnessing the Potential of Artificial Intelligence to Promote Environmental Sustainability provides a comprehensive examination of how AI is transforming environmental conservation and sustainability efforts. This scholarly work delves into cutting-edge AI technologies-such as automation, data analytics, and machine learning-and explores their potential to address pressing environmental challenges. Through in-depth analysis and practical case studies, the book demonstrates how AI can enhance resource management, support sustainable practices, and improve environmental monitoring.Beyond technical solutions, the authors engage with the ethical considerations and potential risks of deploying AI in environmental contexts. Issues such as fairness, transparency, and accountability in AI systems are explored, along with the need for regulatory frameworks to mitigate negative impacts. An essential resource for researchers, professionals, policymakers, and anyone interested in the intersection of technology and environmental stewardship, this contributed work offers a roadmap for leveraging AI to foster a sustainable future, emphasising the crucial role of advanced technologies in addressing global environmental challenges.

Harnessing the Potential of Artificial Intelligence to Promote Environmental Sustainability provides a comprehensive examination of how AI is transforming environmental conservation and sustainability efforts. This scholarly work delves into cutting-edge AI technologies—such as automation, data analytics, and machine learning—and explores their potential to address pressing environmental challenges. Through in-depth analysis and practical case studies, the book demonstrates how AI can enhance resource management, support sustainable practices, and improve environmental monitoring.Beyond technical solutions, the authors engage with the ethical considerations and potential risks of deploying AI in environmental contexts. Issues such as fairness, transparency, and accountability in AI systems are explored, along with the need for regulatory frameworks to mitigate negative impacts. An essential resource for researchers, professionals, policymakers, and anyone interested in the intersection of technology and environmental stewardship, this contributed work offers a roadmap for leveraging AI to foster a sustainable future, emphasising the crucial role of advanced technologies in addressing global environmental challenges.

Harnessing the Potential of Artificial Intelligence to Promote Environmental Sustainability provides a comprehensive examination of how AI is transforming environmental conservation and sustainability efforts. This scholarly work delves into cutting-edge AI technologies-such as automation, data analytics, and machine learning-and explores their potential to address pressing environmental challenges. Through in-depth analysis and practical case studies, the book demonstrates how AI can enhance resource management, support sustainable practices, and improve environmental monitoring.Beyond technical solutions, the authors engage with the ethical considerations and potential risks of deploying AI in environmental contexts. Issues such as fairness, transparency, and accountability in AI systems are explored, along with the need for regulatory frameworks to mitigate negative impacts. An essential resource for researchers, professionals, policymakers, and anyone interested in the intersection of technology and environmental stewardship, this contributed work offers a roadmap for leveraging AI to foster a sustainable future, emphasising the crucial role of advanced technologies in addressing global environmental challenges.

The goal of this book is topresent advances that discuss alternative Evolutionary Computation (EC) developmentsand non-conventional operators which have proved to be effective in the solutionof several complex problems. The book has been structured so that each chaptercan be read independently from the others. The book contains nine chapters withthe following themes: 1) Introduction, 2) the Social Spider Optimization (SSO),3) the States of Matter Search (SMS), 4) the collective animal behavior (CAB)algorithm, 5) the Allostatic Optimization (AO) method, 6) the Locust Search(LS) algorithm, 7) the Adaptive Population with Reduced Evaluations (APRE)method, 8) the multimodal CAB, 9) the constrained SSO method.

The goal of this book is topresent advances that discuss alternative Evolutionary Computation (EC) developmentsand non-conventional operators which have proved to be effective in the solutionof several complex problems. The book has been structured so that each chaptercan be read independently from the others. The book contains nine chapters withthe following themes: 1) Introduction, 2) the Social Spider Optimization (SSO),3) the States of Matter Search (SMS), 4) the collective animal behavior (CAB)algorithm, 5) the Allostatic Optimization (AO) method, 6) the Locust Search(LS) algorithm, 7) the Adaptive Population with Reduced Evaluations (APRE)method, 8) the multimodal CAB, 9) the constrained SSO method.