The Power of Data: Driving Climate Change with Data Science and Artificial Intelligence Innovations

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Publisher : Springer Nature
ISBN 13 : 3031224566
Total Pages : 255 pages
Book Rating : 4.0/5 (312 download)

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Book Synopsis The Power of Data: Driving Climate Change with Data Science and Artificial Intelligence Innovations by : Aboul Ella Hassanien

Download or read book The Power of Data: Driving Climate Change with Data Science and Artificial Intelligence Innovations written by Aboul Ella Hassanien and published by Springer Nature. This book was released on 2023-03-11 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the advances of artificial intelligence and data sciences in climate change and provides the power of the climate data that is used as inputs to artificial intelligence systems. It is a good resource for researchers and professionals who work in the field of data sciences, artificial intelligence, and climate change applications.

Encyclopedia of Data Science and Machine Learning

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Publisher : IGI Global
ISBN 13 : 1799892212
Total Pages : 3296 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Encyclopedia of Data Science and Machine Learning by : Wang, John

Download or read book Encyclopedia of Data Science and Machine Learning written by Wang, John and published by IGI Global. This book was released on 2023-01-20 with total page 3296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.

Data-Driven Innovation

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Author :
Publisher : Routledge
ISBN 13 : 100032916X
Total Pages : 117 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Data-Driven Innovation by : Michael Moesgaard Andersen

Download or read book Data-Driven Innovation written by Michael Moesgaard Andersen and published by Routledge. This book was released on 2021-03-02 with total page 117 pages. Available in PDF, EPUB and Kindle. Book excerpt: Today, innovation does not just occur in large and incumbent R&D organizations. Instead, it often emerges from the start-up community. In the new innovation economy, the key is to quickly find pieces of innovation, some of which may already be developed. Therefore, there is the need for more advanced means of searching and identifying innovation wherever it may occurs. We point to the importance of data-driven innovation based on digital platforms, as their footprints are growing rapidly and in sync with the shift from analogue to digital innovation workflows. This book offers companies insights on paths to business success and tools that will help them find the right route through the various options when it comes to the digital platforms where innovations may be discovered and from which value may be appropriated. The world hungers for growth and one of the most important vehicles for growth is innovation. In light of the new digital platforms from which data-driven innovation can be extracted, major parts of analogue workflows will be substituted with digital workflows. Data-driven innovation and digital innovation workflows are here to stay. Are you?

Towards Ethical and Socially Responsible Explainable AI

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Publisher : Springer Nature
ISBN 13 : 3031664892
Total Pages : 381 pages
Book Rating : 4.0/5 (316 download)

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Book Synopsis Towards Ethical and Socially Responsible Explainable AI by : Mohammad Amir Khusru Akhtar

Download or read book Towards Ethical and Socially Responsible Explainable AI written by Mohammad Amir Khusru Akhtar and published by Springer Nature. This book was released on with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Artificial Intelligence for Environmental Sustainability and Green Initiatives

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Publisher : Springer Nature
ISBN 13 : 3031634519
Total Pages : 361 pages
Book Rating : 4.0/5 (316 download)

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Book Synopsis Artificial Intelligence for Environmental Sustainability and Green Initiatives by : Aboul Ella Hassanien

Download or read book Artificial Intelligence for Environmental Sustainability and Green Initiatives written by Aboul Ella Hassanien and published by Springer Nature. This book was released on with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Water-Soil-Plant-Animal Nexus in the Era of Climate Change

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Publisher : IGI Global
ISBN 13 : 1668498405
Total Pages : 504 pages
Book Rating : 4.6/5 (684 download)

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Book Synopsis Water-Soil-Plant-Animal Nexus in the Era of Climate Change by : Karmaoui, Ahmed

Download or read book Water-Soil-Plant-Animal Nexus in the Era of Climate Change written by Karmaoui, Ahmed and published by IGI Global. This book was released on 2023-12-18 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: Water, soil, plants, and animals are the main pillars that support global food security. Plants grow using nutrients from water and soil resources and then used by animals which affects them consequently. Water is the essential condition of life for all living beings, and soil is its support and a crucial reservoir. The interactions between the Water-Soil-Plant-Animal nexus and climate change are of increasing concern to scholars, decision-makers, and researchers. The impacts of climate change on these resources include water and soil quality degradation, infectious disease, shortage, desertification, and erosion. These impacts are accelerated due to human pressure through over-use and pollution. Water-Soil-Plant-Animal Nexus in the Era of Climate Change includes relevant theoretical approaches, empirical research, and bibliometric and bibliographic methods to bring together affordable methods and techniques to optimize the use of the nexus in the context of climate change. It presents an inventory of techniques and practices in the field, and introduces an opportunity to discuss the strengths and weaknesses of these techniques, making it ideal for scholars, researchers, planners, and decision-makers.

AI Applications for Clean Energy and Sustainability

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Publisher : IGI Global
ISBN 13 :
Total Pages : 485 pages
Book Rating : 4.3/5 (693 download)

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Book Synopsis AI Applications for Clean Energy and Sustainability by : Riswandi, Budi Agus

Download or read book AI Applications for Clean Energy and Sustainability written by Riswandi, Budi Agus and published by IGI Global. This book was released on 2024-08-16 with total page 485 pages. Available in PDF, EPUB and Kindle. Book excerpt: The global demand for clean energy solutions the urgency of addressing climate change continue to intensify, and as such, the need for innovative approaches becomes increasingly paramount. However, navigating the complex landscape of clean energy production and sustainability presents significant challenges. Traditional methods often fall short in efficiently optimizing renewable energy systems and mitigating environmental impacts. Moreover, the integration of artificial intelligence (AI) into the energy sector remains underexplored, despite its potential to revolutionize operations and drive sustainable development. AI Applications for Clean Energy and Sustainability emerges, working to tackle these pressing issues. This comprehensive volume delves into the transformative power of AI in revolutionizing clean energy production, distribution, and management. By harnessing machine learning algorithms, data analytics, and optimization techniques, the book offers innovative solutions to enhance the efficiency, reliability, and scalability of renewable energy systems. Through real-world case studies and practical examples, it illustrates AI's potential to optimize energy infrastructure, monitor marine ecosystems, and predict climate change impacts, thereby paving the way for a more sustainable future.

Data-Driven Innovation for Intelligent Technology

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Publisher : Springer Nature
ISBN 13 : 3031542770
Total Pages : 255 pages
Book Rating : 4.0/5 (315 download)

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Book Synopsis Data-Driven Innovation for Intelligent Technology by : Hiram Ponce

Download or read book Data-Driven Innovation for Intelligent Technology written by Hiram Ponce and published by Springer Nature. This book was released on with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Data-Driven Innovation for Intelligent Technology

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Author :
Publisher : Springer
ISBN 13 : 9783031542763
Total Pages : 0 pages
Book Rating : 4.5/5 (427 download)

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Book Synopsis Data-Driven Innovation for Intelligent Technology by : Hiram Ponce

Download or read book Data-Driven Innovation for Intelligent Technology written by Hiram Ponce and published by Springer. This book was released on 2024-04-28 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: ​ This book focuses on new perspectives and applications of data-driven innovation technologies, applied artificial intelligence, applied machine learning and deep learning, data science, and topics related to transforming data into value. It includes theory and use cases to help readers understand the basics of data-driven innovation and to highlight the applicability of the technologies. It emphasizes how the data lifecycle is applied in current technologies in different business domains and industries, such as advanced materials, healthcare and medicine, resource optimization, control and automation, among others. This book is useful for anyone interested in data-driven innovation for smart technologies, as well as those curious in implementing cutting-edge technologies to solve impactful artificial intelligence, data science, and related information technology and communication problems.

Advanced Technology for Smart Environment and Energy

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Publisher : Springer Nature
ISBN 13 : 3031508718
Total Pages : 326 pages
Book Rating : 4.0/5 (315 download)

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Book Synopsis Advanced Technology for Smart Environment and Energy by : Jamal Mabrouki

Download or read book Advanced Technology for Smart Environment and Energy written by Jamal Mabrouki and published by Springer Nature. This book was released on with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Disaster and Climate Risk Education

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Publisher : Springer Nature
ISBN 13 : 9819759870
Total Pages : 438 pages
Book Rating : 4.8/5 (197 download)

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Book Synopsis Disaster and Climate Risk Education by : Ayse Yildiz

Download or read book Disaster and Climate Risk Education written by Ayse Yildiz and published by Springer Nature. This book was released on with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Big Data, Artificial Intelligence, and Data Analytics in Climate Change Research

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Publisher : Springer Nature
ISBN 13 : 9819716853
Total Pages : 339 pages
Book Rating : 4.8/5 (197 download)

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Book Synopsis Big Data, Artificial Intelligence, and Data Analytics in Climate Change Research by : Gaurav Tripathi

Download or read book Big Data, Artificial Intelligence, and Data Analytics in Climate Change Research written by Gaurav Tripathi and published by Springer Nature. This book was released on with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt:

The Elements of Big Data Value

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Publisher : Springer Nature
ISBN 13 : 3030681769
Total Pages : 399 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis The Elements of Big Data Value by : Edward Curry

Download or read book The Elements of Big Data Value written by Edward Curry and published by Springer Nature. This book was released on 2021-08-01 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book presents the foundations of the Big Data research and innovation ecosystem and the associated enablers that facilitate delivering value from data for business and society. It provides insights into the key elements for research and innovation, technical architectures, business models, skills, and best practices to support the creation of data-driven solutions and organizations. The book is a compilation of selected high-quality chapters covering best practices, technologies, experiences, and practical recommendations on research and innovation for big data. The contributions are grouped into four parts: · Part I: Ecosystem Elements of Big Data Value focuses on establishing the big data value ecosystem using a holistic approach to make it attractive and valuable to all stakeholders. · Part II: Research and Innovation Elements of Big Data Value details the key technical and capability challenges to be addressed for delivering big data value. · Part III: Business, Policy, and Societal Elements of Big Data Value investigates the need to make more efficient use of big data and understanding that data is an asset that has significant potential for the economy and society. · Part IV: Emerging Elements of Big Data Value explores the critical elements to maximizing the future potential of big data value. Overall, readers are provided with insights which can support them in creating data-driven solutions, organizations, and productive data ecosystems. The material represents the results of a collective effort undertaken by the European data community as part of the Big Data Value Public-Private Partnership (PPP) between the European Commission and the Big Data Value Association (BDVA) to boost data-driven digital transformation.

Driving Digital Transformation Through Data and AI

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Publisher : Kogan Page
ISBN 13 : 9781789665413
Total Pages : 288 pages
Book Rating : 4.6/5 (654 download)

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Book Synopsis Driving Digital Transformation Through Data and AI by : Alexander Borek

Download or read book Driving Digital Transformation Through Data and AI written by Alexander Borek and published by Kogan Page. This book was released on 2020-09-29 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Avoid being left behind and make data science and artificial intelligence a profitable part of your business with this practical guide to product delivery.

Implementing Data-Driven Strategies in Smart Cities

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Publisher : Elsevier
ISBN 13 : 0128211237
Total Pages : 258 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis Implementing Data-Driven Strategies in Smart Cities by : Didier Grimaldi

Download or read book Implementing Data-Driven Strategies in Smart Cities written by Didier Grimaldi and published by Elsevier. This book was released on 2021-09-18 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Implementing Data-Driven Strategies in Smart Cities is a guidebook and roadmap for practitioners seeking to operationalize data-driven urban interventions. The book opens by exploring the revolution that big data, data science, and the Internet of Things are making feasible for the city. It explores alternate topologies, typologies, and approaches to operationalize data science in cities, drawn from global examples including top-down, bottom-up, greenfield, brownfield, issue-based, and data-driven. It channels and expands on the classic data science model for data-driven urban interventions – data capture, data quality, cleansing and curation, data analysis, visualization and modeling, and data governance, privacy, and confidentiality. Throughout, illustrative case studies demonstrate successes realized in such diverse cities as Barcelona, Cologne, Manila, Miami, New York, Nancy, Nice, São Paulo, Seoul, Singapore, Stockholm, and Zurich. Given the heavy emphasis on global case studies, this work is particularly suitable for any urban manager, policymaker, or practitioner responsible for delivering technological services for the public sector from sectors as diverse as energy, transportation, pollution, and waste management. Explores numerous specific urban interventions drawn from global case studies, helping readers understand real urban challenges and create data-driven solutions Provides a step-by-step and applied holistic guide and methodology for immediate application in the reader’s own business agenda Presents cutting edge technology presentation with coverage of innovations such as the Internet of Things, robotics, 5G, edge/fog computing, blockchain, intelligent transport systems, and connected-automated mobility

Visualization Techniques for Climate Change with Machine Learning and Artificial Intelligence

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Author :
Publisher : Elsevier
ISBN 13 : 0323997155
Total Pages : 500 pages
Book Rating : 4.3/5 (239 download)

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Book Synopsis Visualization Techniques for Climate Change with Machine Learning and Artificial Intelligence by : Arun Lal Srivastav

Download or read book Visualization Techniques for Climate Change with Machine Learning and Artificial Intelligence written by Arun Lal Srivastav and published by Elsevier. This book was released on 2022-11-11 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: Visualization Techniques for Climate Change with Machine Learning and Artificial Intelligence covers computer-aided artificial intelligence and machine learning technologies as related to the impacts of climate change and its potential to prevent/remediate the effects. As such, different types of algorithms, mathematical relations and software models may help us to understand our current reality, predict future weather events and create new products and services to minimize human impact, chances of improving and saving lives and creating a healthier world. This book covers different types of tools for the prediction of climate change and alternative systems which can reduce the levels of threats observed by climate change scientists. Moreover, the book will help to achieve at least one of 17 sustainable development goals i.e., climate action. Includes case studies on the application of AI and machine learning for monitoring climate change effects and management Features applications of software and algorithms for modeling and forecasting climate change Shows how real-time monitoring of specific factors (temperature, level of greenhouse gases, rain fall patterns, etc.) are responsible for climate change and possible mitigation efforts to achieve environmental sustainability

Computational Intelligent Data Analysis for Sustainable Development

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Author :
Publisher : CRC Press
ISBN 13 : 1439895945
Total Pages : 443 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Computational Intelligent Data Analysis for Sustainable Development by : Ting Yu

Download or read book Computational Intelligent Data Analysis for Sustainable Development written by Ting Yu and published by CRC Press. This book was released on 2013-04-04 with total page 443 pages. Available in PDF, EPUB and Kindle. Book excerpt: Going beyond performing simple analyses, researchers involved in the highly dynamic field of computational intelligent data analysis design algorithms that solve increasingly complex data problems in changing environments, including economic, environmental, and social data. Computational Intelligent Data Analysis for Sustainable Development presents novel methodologies for automatically processing these types of data to support rational decision making for sustainable development. Through numerous case studies and applications, it illustrates important data analysis methods, including mathematical optimization, machine learning, signal processing, and temporal and spatial analysis, for quantifying and describing sustainable development problems. With a focus on integrated sustainability analysis, the book presents a large-scale quadratic programming algorithm to expand high-resolution input-output tables from the national scale to the multinational scale to measure the carbon footprint of the entire trade supply chain. It also quantifies the error or dispersion between different reclassification and aggregation schemas, revealing that aggregation errors have a high concentration over specific regions and sectors. The book summarizes the latest contributions of the data analysis community to climate change research. A profuse amount of climate data of various types is available, providing a rich and fertile playground for future data mining and machine learning research. The book also pays special attention to several critical challenges in the science of climate extremes that are not handled by the current generation of climate models. It discusses potential conceptual and methodological directions to build a close integration between physical understanding, or physics-based modeling, and data-driven insights. The book then covers the conservation of species and ecologically valuable land. A case study on the Pennsylvania Dirt and Gravel Roads Program demonstrates that multiple-objective linear programming is a more versatile and efficient approach than the widely used benefit targeting selection process. Moving on to renewable energy and the need for smart grids, the book explores how the ongoing transformation to a sustainable energy system of renewable sources leads to a paradigm shift from demand-driven generation to generation-driven demand. It shows how to maximize renewable energy as electricity by building a supergrid or mixing renewable sources with demand management and storage. It also presents intelligent data analysis for real-time detection of disruptive events from power system frequency data collected using an existing Internet-based frequency monitoring network as well as evaluates a set of computationally intelligent techniques for long-term wind resource assessment. In addition, the book gives an example of how temporal and spatial data analysis tools are used to gather knowledge about behavioral data and address important social problems such as criminal offenses. It also applies constraint logic programming to a planning problem: the environmental and social impact assessment of the regional energy plan of the Emilia-Romagna region of Italy. Sustainable development problems, such as global warming, resource shortages, global species loss, and pollution, push researchers to create powerful data analysis approaches that analysts can then use to gain insight into these issues to support rational decision making. This volume shows both the data analysis and sustainable development communities how to use intelligent data analysis tools to address practical problems and encourages researchers to develop better methods.