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Artificial Intelligence in the Energy
Industry

Artificial Intelligence in the Energy Industry

Theory, Case Studies, and Applications

Expert reference on building surrogate models, optimization using them, prediction uncertainty associate with them, and their potential failure, with practical implementation in MATLAB Surrogate Modeling and Optimization explains the meaning of different surrogate models and provides an in-depth understanding of such surrogates, emphasizing how much uncertainty is associated with them, and when and how a surrogate model can fail in approximating complex functions and helping readers understand theory through practical implementation in MATLAB. This book enables readers to obtain an accurate approximate function using as few samples as possible, thereby allowing them to replace expensive computer simulations and experiments during design optimization, sensitivity analysis, and/or uncertainty quantification. The book is organized into three parts. Part I introduces the basics of surrogate modeling. Part II reviews various theories and algorithms of design optimization. Part III presents advanced topics in surrogate modeling, including the Kriging surrogate, neural network models, multi-fidelity surrogates, and efficient global optimization using Kriging surrogates. The book is divided into 10 chapters. Each chapter contains about 10 examples and 20 exercise problems. Lecture slides and a solution manual for exercise problems are available for instructors on a companion website. Sample topics discussed in Surrogate Modeling and Optimization include: <ul> <li>Various designs of experiments, such as those developed for linear and quadratic polynomial response surfaces (PRS) in a boxlike design space</li> <li>Criteria for constrained and unconstrained optimization and the most important optimization theories</li> <li>Various numerical algorithms for gradient-based optimization</li> <li>Gradient-free optimization algorithms, often referred to as global search algorithms, which do not require gradient or Hessian information</li> <li>Detailed explanations and implementation on Kriging surrogate, often referred to as Gaussian Process, especially when samples include noise</li> <li>The combination of a small number of high-fidelity samples with many low-fidelity samples to improve prediction accuracy</li> <li>Neural network models, focusing on training uncertainty and its effect on prediction uncertainty</li> <li>Efficient global optimization using either polynomial response surfaces or Kriging surrofates</li> </ul> Surrogate Modeling and Optimization is an essential learning companion for senior-level undergraduate and graduate students in all engineering disciplines, including mechanical, aerospace, civil, biomedical, and electrical engineering. The book is also valuable for industrial practitioners who apply the surrogate model to solve their optimization problems.

Theories, Applications, and Limitations

Surrogate Modeling and Optimization

Driving Business Success and Profit Through Enterprise Automation and AI Agents

Untangling AI

Design for Healing Spaces

Therapeutic Gardens

Building and Deploying AI Applications at Scale

ML and Generative AI in the Data Lakehouse

Vegetable Oil in Energy, Volume 1: Biofuel Technology examines the conversion processes involved in the production of biofuels from vegetable oils. With a strong focus on methodologies and protocols, the book provides step-by-step guidance on a comprehensive range of production pathways for liquid and gaseous biofuels. The first part of the book provides an overview of present vegetable oil production. Subsequent chapters describe the key production pathways, including pyrolysis, decarboxylation, deoxygenation, catalytic cracking processes, esterification, trans-esterification, anaerobic digestion, catalytic pyrolysis, and more. The economic potential of different vegetable oil feedstocks is discussed within each chapter. Finally, chapters are dedicated to sustainability, examining the environmental and socioeconomic impact of production, with an emphasis on GHG emission reduction. This book provides readers with the latest developments in the production of biofuels from vegetable oils, which will be of interest to students, researchers, and industry professionals involved in bioenergy and renewable energy, and may be of interest to interdisciplinary teams working across biotechnology, chemistry, chemical engineering, environmental science and sustainability sciences.

Biofuel Technology

Vegetable Oil in Energy, Volume 1

Synthesis Lectures on Technology and Health

<div>This book provides a comprehensive overview of palliative care digital health by covering current developments, methodology, clinical relevance, research priorities, ethical issues, and policy related to technological innovations for those with serious illness. This type of book does not currently exist in the literature, as previous work primarily focuses on digital health for early identification of disease and facilitating self-care or ‘aging in place’ practices. This book addresses the lack of focus on digital health for people with palliative care needs. This book has a special focus on the needs of individuals as their health worsens throughout their illness. Consequently, the reader will benefit from this book’s focus on the science, methodology, application, and practicality of digital health developments in palliative care.</div>
<div>This book explores the barriers that prevent the meaningful use of digital health in palliative care, including expenses, interoperability issues, data privacy and security concerns, lack of effectiveness and equity, and the concern that technology may reduce face-to-face consultations between patients and clinicians. There is an overall lack of consensus about digital health research priorities in palliative care, and a lack of theories about how these technologies might improve care outcomes. Therefore, this book emphasizes the importance of identifying, discussing, and debating how technological innovations can be meaningfully used to ensure that frail people have appropriate access to palliative care services. Consequently, this book begins the conversation about articulating digital health research priorities in palliative care to determine how finite resources should be allocated to a field saturated with rapidly developing innovation.</div>

Technologies in Palliative Care for Older People

Shortest Histories

The Shortest History of AI

Building a Program for Strategy and Oversight

Practical AI Governance

My Journey and the Future of Energy

Inexhaustible

Modern Trends In Financial Engineering

Multiscale Financial Data Analytics and Machine Learning offers a systematic and comprehensive study on the multiscale approach to financial data analytics and machine learning. This book covers an array of multiscale methods to discover the properties of various timescales embedded in a financial time series, including noise-assisted empirical mode decomposition methods. Important interpretable multiscale outputs from the estimation are recognized as a new set of features that can be used for machine learning. The feature selection problem for machine learning is examined in this volume.This book offers an applied quantitative approach that combines novel analytical methodologies and practical applications to a wide array of examples with real-world data. It is self-contained and organized in its presentation. The explanations of the methodologies are both accessible and detailed enough to capture the interest of the curious student or researcher. Step-by-step descriptions of the algorithms are provided for straightforward implementation.

Multiscale Financial Data Analytics And Machine Learning

Beck international

The Book
Artificial Intelligence will profoundly shape the future economy and society. Whereas the potential benefits are notable and desirable, the risk of serious harm is considerable. The new EU AI Act 2024/1689 therefore seeks to provide a legal framework to regulate AI systems in the EU.
Written by an international team of experts, this Article-by-Article Commentary provides a comprehensive analysis and explanation of each of the provisions of the AI Act to assist in the interpretation and application. Each commentary follows a clear and uniform structure, also providing key information on the function and context of each provision. Where appropriate, practice tips are also given.

The Advantages at a GlanceComprehensive analysisInternational team of renowned expertsClear and uniform structure
The Target Group
For in-house counsel, legal practitioners, scholars, supervisory authorities, industry groups.

The Book
Artificial Intelligence will profoundly shape the future economy and society. Whereas the potential benefits are notable and desirable, the risk of serious harm is considerable. The new EU AI Act 2024/1689 therefore seeks to provide a legal framework to regulate AI systems in the EU.
Written by an international team of experts, this Article-by-Article Commentary provides a comprehensive analysis and explanation of each of the provisions of the AI Act to assist in the interpretation and application. Each commentary follows a clear and uniform structure, also providing key information on the function and context of each provision. Where appropriate, practice tips are also given.

The Advantages at a GlanceComprehensive analysisInternational team of renowned expertsClear and uniform structure
The Target Group
For in-house counsel, legal practitioners, scholars, supervisory authorities, industry groups.

Article-by-Article Commentary

Artificial Intelligence Act

Impacts, Detection and its Remediation

Xenobiotics in Environment

Artificial Intelligence in the Energy Industry

Weitere Titel zum Thema