Machine Learning and Data Science Techniques for Effective Government Service Delivery
Machine Learning and Data Science Techniques for Effective Government Service Delivery

Author: Ogunleye, Olalekan Samuel

Publisher: IGI Global

Published: 2024-03-27

Total Pages: 358

ISBN-13: 1668497182

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In our data-rich era, extracting meaningful insights from the vast amount of information has become a crucial challenge, especially in government service delivery where informed decisions are paramount. Traditional approaches struggle with the enormity of data, highlighting the need for a new approach that integrates data science and machine learning. The book, Machine Learning and Data Science Techniques for Effective Government Service Delivery, becomes a vital resource in this transformation, offering a deep understanding of these technologies and their applications. Within the complex landscape of modern governance, this book stands as a solution-oriented guide. Recognizing data's value in the 21st century, it navigates the world of data science and machine learning, enhancing the mechanics of government service. By addressing citizens' evolving needs, these advanced methods counter inefficiencies in traditional systems. Tailored for experts across technology, academia, and government, the book bridges theory and practicality. Covering foundational concepts and innovative applications, it explores the potential of data-driven decision-making for a more efficient and citizen-centric government future.

Digital Transformation and Sustainable Development in Cities and Organizations
Digital Transformation and Sustainable Development in Cities and Organizations

Author: Theofanidis, Faidon

Publisher: IGI Global

Published: 2024-02-27

Total Pages: 321

ISBN-13:

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In the ever-evolving landscape of the modern business world, a critical challenge has emerged at the crossroads of digital transformation and sustainable development. Businesses grapple with the need to adapt to digitalization while ensuring their practices align with the imperatives of sustainability. The complexities of this intersection demand innovative solutions and profound insights. Enter Digital Transformation and Sustainable Development in Cities and Organizations – a groundbreaking book that unravels the intricacies of this challenge and provides a comprehensive roadmap for organizations navigating the digital age with a commitment to sustainability. Traditional business models are rendered obsolete as the relentless march of digitalization transforms industries. Amidst this upheaval, the imperative to embrace sustainable practices often takes a backseat. Businesses face the daunting task of navigating this dual challenge – staying technologically relevant while safeguarding the environment and societal well-being. The consequences of overlooking this intersection are profound, leading to missed opportunities for growth and contributing to the escalating threats posed by climate change. The need for a cohesive guide that addresses these intertwined challenges has never been more urgent.

India
India

Author: International Monetary Fund. Asia and Pacific Dept

Publisher: International Monetary Fund

Published: 2017-02-22

Total Pages: 92

ISBN-13: 1475579810

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India: Selected Issues

Biogeochemistry of Trace Elements in Coal and Coal Combustion Byproducts
Biogeochemistry of Trace Elements in Coal and Coal Combustion Byproducts

Author: Kenneth S. Sajwan

Publisher: Springer Science & Business Media

Published: 2011-06-27

Total Pages: 386

ISBN-13: 1461541557

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The research papers in this book present current knowledge of the sources, pathways, behavior, and effects of trace elements in soils, waters, plants, and animals. It is of interest to a variety of readers, including public health and environmental professionals, consultants, and academicians.

Machine Learning and Computer Vision for Renewable Energy
Machine Learning and Computer Vision for Renewable Energy

Author: Acharjya, Pinaki Pratim

Publisher: IGI Global

Published: 2024-05-01

Total Pages: 351

ISBN-13:

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As the world grapples with the urgent need for sustainable energy solutions, the limitations of traditional approaches to renewable energy forecasting become increasingly evident. The demand for more accurate predictions in net load forecasting, line loss predictions, and the seamless integration of hybrid solar and battery storage systems is more critical than ever. In response to this challenge, advanced Artificial Intelligence (AI) techniques are emerging as a solution, promising to revolutionize the renewable energy landscape. Machine Learning and Computer Vision for Renewable Energy presents a deep exploration of AI modeling, analysis, performance prediction, and control approaches dedicated to overcoming the pressing issues in renewable energy systems. Transitioning from the complexities of energy prediction to the promise of advanced technology, the book sets its sights on the game-changing potential of computer vision (CV) in the realm of renewable energy. Amidst the struggle to enhance sustainability across industries, CV technology emerges as a powerful ally, collecting invaluable data from digital photos and videos. This data proves instrumental in achieving better energy management, predicting factors affecting renewable energy, and optimizing overall sustainability. Readers, including researchers, academicians, and students, will find themselves immersed in a comprehensive understanding of the AI approaches and CV methodologies that hold the key to resolving the challenges faced by renewable energy systems.