Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction

Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction
Author: Harsh S. Dhiman,Valentina Emilia Balas
Publsiher: Academic Press
Total Pages: 216
Release: 2020-01-20
ISBN 10: 0128213531
ISBN 13: 9780128213537
Language: EN, FR, DE, ES & NL

Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction Book Review:

Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction provides an up-to- date overview on the broad area of wind generation and forecasting, with a focus on the role and need of Machine Learning in this emerging field of knowledge. Various regression models and signal decomposition techniques are presented and analyzed, including least-square, twin support and random forest regression, all with supervised Machine Learning. The specific topics of ramp event prediction and wake interactions are addressed in this book, along with forecasted performance. Wind speed forecasting has become an essential component to ensure power system security, reliability and safe operation, making this reference useful for all researchers and professionals researching renewable energy, wind energy forecasting and generation. Features various supervised machine learning based regression models Offers global case studies for turbine wind farm layouts Includes state-of-the-art models and methodologies in wind forecasting

Soft Computing Applications

Soft Computing Applications
Author: Valentina Emilia Balas,Lakhmi C. Jain,Marius Mircea Balas,Shahnaz N. Shahbazova
Publsiher: Springer Nature
Total Pages: 438
Release: 2020-08-14
ISBN 10: 3030519929
ISBN 13: 9783030519926
Language: EN, FR, DE, ES & NL

Soft Computing Applications Book Review:

This book presents the proceedings of the 8th International Workshop on Soft Computing Applications, SOFA 2018, held on 13–15 September 2018 in Arad, Romania. The workshop was organized by Aurel Vlaicu University of Arad, in conjunction with the Institute of Computer Science, Iasi Branch of the Romanian Academy, IEEE Romanian Section, Romanian Society of Control Engineering and Technical Informatics – Arad Section, General Association of Engineers in Romania – Arad Section and BTM Resources Arad. The papers included in these proceedings, published post-conference, cover the research including Knowledge-Based Technologies for Web Applications, Cloud Computing, Security Algorithms and Computer Networks, Business Process Management, Computational Intelligence in Education and Modelling and Applications in Textiles and many other areas related to the Soft Computing. The book is directed to professors, researchers, and graduate students in area of soft computing techniques and applications.

Computational Sustainability

Computational Sustainability
Author: Jörg Lässig,Kristian Kersting,Katharina Morik
Publsiher: Springer
Total Pages: 276
Release: 2016-04-20
ISBN 10: 3319318586
ISBN 13: 9783319318585
Language: EN, FR, DE, ES & NL

Computational Sustainability Book Review:

The book at hand gives an overview of the state of the art research in Computational Sustainability as well as case studies of different application scenarios. This covers topics such as renewable energy supply, energy storage and e-mobility, efficiency in data centers and networks, sustainable food and water supply, sustainable health, industrial production and quality, etc. The book describes computational methods and possible application scenarios.

Advanced Control and Optimization Paradigms for Wind Energy Systems

Advanced Control and Optimization Paradigms for Wind Energy Systems
Author: Radu-Emil Precup,Tariq Kamal,Syed Zulqadar Hassan
Publsiher: Springer
Total Pages: 257
Release: 2019-02-07
ISBN 10: 9811359954
ISBN 13: 9789811359958
Language: EN, FR, DE, ES & NL

Advanced Control and Optimization Paradigms for Wind Energy Systems Book Review:

This book presents advanced studies on the conversion efficiency, mechanical reliability, and the quality of power related to wind energy systems. The main concern regarding such systems is reconciling the highly intermittent nature of the primary source (wind speed) with the demand for high-quality electrical energy and system stability. This means that wind energy conversion within the standard parameters imposed by the energy market and power industry is unachievable without optimization and control. The book discusses the rapid growth of control and optimization paradigms and applies them to wind energy systems: new controllers, new computational approaches, new applications, new algorithms, and new obstacles.

Integration of Large Scale Renewable Energy into Bulk Power Systems

Integration of Large Scale Renewable Energy into Bulk Power Systems
Author: Pengwei Du,Ross Baldick,Aidan Tuohy
Publsiher: Springer
Total Pages: 337
Release: 2017-06-15
ISBN 10: 3319555812
ISBN 13: 9783319555812
Language: EN, FR, DE, ES & NL

Integration of Large Scale Renewable Energy into Bulk Power Systems Book Review:

This book outlines the challenges that increasing amounts of renewable and distributed energy represent when integrated into established electricity grid infrastructures, offering a range of potential solutions that will support engineers, grid operators, system planners, utilities, and policymakers alike in their efforts to realize the vision of moving toward greener, more secure energy portfolios. Covering all major renewable sources, from wind and solar, to waste energy and hydropower, the authors highlight case studies of successful integration scenarios to demonstrate pathways toward overcoming the complexities created by variable and distributed generation.

Grokking Machine Learning

Grokking Machine Learning
Author: Serrano G. Luis
Publsiher: Manning Publications
Total Pages: 350
Release: 2020-11-24
ISBN 10: 9781617295911
ISBN 13: 1617295914
Language: EN, FR, DE, ES & NL

Grokking Machine Learning Book Review:

It's time to dispel the myth that machine learning is difficult. Grokking Machine Learning teaches you how to apply ML to your projects using only standard Python code and high school-level math. No specialist knowledge is required to tackle the hands-on exercises using readily-available machine learning tools! In Grokking Machine Learning, expert machine learning engineer Luis Serrano introduces the most valuable ML techniques and teaches you how to make them work for you. Practical examples illustrate each new concept to ensure you’re grokking as you go. You’ll build models for spam detection, language analysis, and image recognition as you lock in each carefully-selected skill. Packed with easy-to-follow Python-based exercises and mini-projects, this book sets you on the path to becoming a machine learning expert. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

Decision and Control in Hybrid Wind Farms

Decision and Control in Hybrid Wind Farms
Author: Harsh S. Dhiman,Dipankar Deb
Publsiher: Springer Nature
Total Pages: 140
Release: 2019-09-28
ISBN 10: 9811502757
ISBN 13: 9789811502750
Language: EN, FR, DE, ES & NL

Decision and Control in Hybrid Wind Farms Book Review:

This book focuses on two of the most important aspects of wind farm operation: decisions and control. The first part of the book deals with decision-making processes, and explains that hybrid wind farm operation is governed by a set of alternatives that the wind farm operator must choose from in order to achieve optimal delivery of wind power to the utility grid. This decision-making is accompanied by accurate forecasts of wind speed, which must be known beforehand. Errors in wind forecasting can be compensated for by pumping power from a reserve capacity to the grid using a battery energy storage system (BESS). Alternatives based on penalty cost are assessed using certain criteria, and MCDM methods are used to evaluate the best choice. Further, considering the randomness in the dynamic phenomenon in wind farms, a fuzzy MCDM approach is applied during the decision-making process to evaluate the best alternative for hybrid wind farm operation. Case studies from wind farms in the USA are presented, together with numerical solutions to the problem. In turn, the second part deals with the control aspect, and especially with yaw angle control, which facilitates power maximization at wind farms. A novel transfer function-based methodology is presented that controls the wake center of the upstream turbine(s); lidar-based numerical simulation is carried out for wind farm layouts; and an adaptive control strategy is implemented to achieve the desired yaw angle for upstream turbines. The proposed methodology is tested for two wind farm layouts. Wake management is also implemented for hybrid wind farms where BESS life enhancement is studied. The effect of yaw angle on the operational cost of BESS is assessed, and case studies for wind farm datasets from the USA and Denmark are discussed. Overall, the book provides a comprehensive guide to decision and control aspects for hybrid wind farms, which are particularly important from an industrial standpoint.

Engineering Research Methodology

Engineering Research Methodology
Author: Dipankar Deb,Rajeeb Dey,Valentina E. Balas
Publsiher: Springer
Total Pages: 105
Release: 2018-12-14
ISBN 10: 9811329478
ISBN 13: 9789811329470
Language: EN, FR, DE, ES & NL

Engineering Research Methodology Book Review:

The book covers all the important aspects of research methodology, and addresses the specific requirements of engineering students, such as methods and tools, in detail. It also discusses effective research in engineering today, which requires the ability to undertake literature reviews utilizing different online databases, to attribute credit for any prior work mentioned, to respect intellectual property rights while simultaneously maintaining ethics in research, and much more. Further, the book also considers soft skills like research management and planning, dealing with criticism in research and presentation skills, which are all equally important and need to include in research methodology education. Lastly, it provides the technical knowhow needed to file patents in academia, an important area that is often ignored in research methodology books. The book is a particularly valuable resource for PhD students in India and South East Asia, as research methodology is a part of their coursework.

Advanced Wind Turbine Technology

Advanced Wind Turbine Technology
Author: Weifei Hu
Publsiher: Springer
Total Pages: 349
Release: 2018-05-07
ISBN 10: 3319781669
ISBN 13: 9783319781662
Language: EN, FR, DE, ES & NL

Advanced Wind Turbine Technology Book Review:

This book introduces the current challenges in modern wind turbine analysis, design and development, and provides a comprehensive examination of state-of-the-art technologies from both academia and industry. The twelve information-rich chapters cover a wide range of topics including reliability-based design, computational fluid dynamics, gearbox and bearing analyses, lightning analysis, structural dynamics, health condition monitoring, advanced techniques for field repair, offshore floating wind turbines, advanced turbine control and grid integration, and other emerging technologies. Each chapter begins with the current status of technology in a lucid, is easy-to-follow treatment, then elaborates on the corresponding advanced technology using detailed methodologies, graphs, mathematical models, computational simulations, and experimental instrumentation. Relevant to a broad audience from students and faculty to researchers, manufacturers, and wind energy engineers and designers, the book is ideal for both educational and research needs. Presents the latest developments in reliability-based design optimization, CFD of wind turbines, structural dynamics for wind turbine blades, off-shore floating wind turbines, advanced wind turbine control, and wind power and ramp forecasting for grid integration; Includes techniques for wind turbine gearboxes and bearings, evaluation of lightning strike damage, health condition monitoring and reparation techniques; Illustrates theories and operational considerations using graphics, tables, computational algorithms, simulation models, and experimental instrumentation; Examines unique, innovative technologies for wind energy.

Big Data Analytics Systems Algorithms Applications

Big Data Analytics  Systems  Algorithms  Applications
Author: C.S.R. Prabhu,Aneesh Sreevallabh Chivukula,Aditya Mogadala,Rohit Ghosh,L.M. Jenila Livingston
Publsiher: Springer Nature
Total Pages: 412
Release: 2019-10-14
ISBN 10: 9811500940
ISBN 13: 9789811500947
Language: EN, FR, DE, ES & NL

Big Data Analytics Systems Algorithms Applications Book Review:

This book provides a comprehensive survey of techniques, technologies and applications of Big Data and its analysis. The Big Data phenomenon is increasingly impacting all sectors of business and industry, producing an emerging new information ecosystem. On the applications front, the book offers detailed descriptions of various application areas for Big Data Analytics in the important domains of Social Semantic Web Mining, Banking and Financial Services, Capital Markets, Insurance, Advertisement, Recommendation Systems, Bio-Informatics, the IoT and Fog Computing, before delving into issues of security and privacy. With regard to machine learning techniques, the book presents all the standard algorithms for learning – including supervised, semi-supervised and unsupervised techniques such as clustering and reinforcement learning techniques to perform collective Deep Learning. Multi-layered and nonlinear learning for Big Data are also covered. In turn, the book highlights real-life case studies on successful implementations of Big Data Analytics at large IT companies such as Google, Facebook, LinkedIn and Microsoft. Multi-sectorial case studies on domain-based companies such as Deutsche Bank, the power provider Opower, Delta Airlines and a Chinese City Transportation application represent a valuable addition. Given its comprehensive coverage of Big Data Analytics, the book offers a unique resource for undergraduate and graduate students, researchers, educators and IT professionals alike.

Wind Power Ensemble Forecasting

Wind Power Ensemble Forecasting
Author: André Gensler
Publsiher: Anonim
Total Pages: 329
Release: 2019
ISBN 10: 9783737606370
ISBN 13: 3737606374
Language: EN, FR, DE, ES & NL

Wind Power Ensemble Forecasting Book Review:

Wind Energy Engineering

Wind Energy Engineering
Author: Trevor M. Letcher
Publsiher: Academic Press
Total Pages: 622
Release: 2017-05-11
ISBN 10: 012809429X
ISBN 13: 9780128094297
Language: EN, FR, DE, ES & NL

Wind Energy Engineering Book Review:

Wind Energy Engineering: A Handbook for Onshore and Offshore Wind Turbines is the most advanced, up-to-date and research-focused text on all aspects of wind energy engineering. Wind energy is pivotal in global electricity generation and for achieving future essential energy demands and targets. In this fast moving field this must-have edition starts with an in-depth look at the present state of wind integration and distribution worldwide, and continues with a high-level assessment of the advances in turbine technology and how the investment, planning, and economic infrastructure can support those innovations. Each chapter includes a research overview with a detailed analysis and new case studies looking at how recent research developments can be applied. Written by some of the most forward-thinking professionals in the field and giving a complete examination of one of the most promising and efficient sources of renewable energy, this book is an invaluable reference into this cross-disciplinary field for engineers. Contains analysis of the latest high-level research and explores real world application potential in relation to the developments Uses system international (SI) units and imperial units throughout to appeal to global engineers Offers new case studies from a world expert in the field Covers the latest research developments in this fast moving, vital subject

Machine Learning for Networking

Machine Learning for Networking
Author: Éric Renault,Paul Mühlethaler,Selma Boumerdassi
Publsiher: Springer
Total Pages: 388
Release: 2019-07-08
ISBN 10: 3030199452
ISBN 13: 9783030199456
Language: EN, FR, DE, ES & NL

Machine Learning for Networking Book Review:

This book constitutes the thoroughly refereed proceedings of the First International Conference on Machine Learning for Networking, MLN 2018, held in Paris, France, in November 2018. The 22 revised full papers included in the volume were carefully reviewed and selected from 48 submissions. They present new trends in the following topics: Deep and reinforcement learning; Pattern recognition and classification for networks; Machine learning for network slicing optimization, 5G system, user behavior prediction, multimedia, IoT, security and protection; Optimization and new innovative machine learning methods; Performance analysis of machine learning algorithms; Experimental evaluations of machine learning; Data mining in heterogeneous networks; Distributed and decentralized machine learning algorithms; Intelligent cloud-support communications, resource allocation, energy-aware/green communications, software defined networks, cooperative networks, positioning and navigation systems, wireless communications, wireless sensor networks, underwater sensor networks.

Machine Learning Control Taming Nonlinear Dynamics and Turbulence

Machine Learning Control     Taming Nonlinear Dynamics and Turbulence
Author: Thomas Duriez,Steven L. Brunton,Bernd R. Noack
Publsiher: Springer
Total Pages: 211
Release: 2016-11-02
ISBN 10: 3319406248
ISBN 13: 9783319406244
Language: EN, FR, DE, ES & NL

Machine Learning Control Taming Nonlinear Dynamics and Turbulence Book Review:

This is the first textbook on a generally applicable control strategy for turbulence and other complex nonlinear systems. The approach of the book employs powerful methods of machine learning for optimal nonlinear control laws. This machine learning control (MLC) is motivated and detailed in Chapters 1 and 2. In Chapter 3, methods of linear control theory are reviewed. In Chapter 4, MLC is shown to reproduce known optimal control laws for linear dynamics (LQR, LQG). In Chapter 5, MLC detects and exploits a strongly nonlinear actuation mechanism of a low-dimensional dynamical system when linear control methods are shown to fail. Experimental control demonstrations from a laminar shear-layer to turbulent boundary-layers are reviewed in Chapter 6, followed by general good practices for experiments in Chapter 7. The book concludes with an outlook on the vast future applications of MLC in Chapter 8. Matlab codes are provided for easy reproducibility of the presented results. The book includes interviews with leading researchers in turbulence control (S. Bagheri, B. Batten, M. Glauser, D. Williams) and machine learning (M. Schoenauer) for a broader perspective. All chapters have exercises and supplemental videos will be available through YouTube.

The Nature of Statistical Learning Theory

The Nature of Statistical Learning Theory
Author: Vladimir N. Vapnik
Publsiher: Springer Science & Business Media
Total Pages: 188
Release: 2013-04-17
ISBN 10: 1475724403
ISBN 13: 9781475724400
Language: EN, FR, DE, ES & NL

The Nature of Statistical Learning Theory Book Review:

The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. It considers learning from the general point of view of function estimation based on empirical data. Omitting proofs and technical details, the author concentrates on discussing the main results of learning theory and their connections to fundamental problems in statistics. These include: - the general setting of learning problems and the general model of minimizing the risk functional from empirical data - a comprehensive analysis of the empirical risk minimization principle and shows how this allows for the construction of necessary and sufficient conditions for consistency - non-asymptotic bounds for the risk achieved using the empirical risk minimization principle - principles for controlling the generalization ability of learning machines using small sample sizes - introducing a new type of universal learning machine that controls the generalization ability.

Intelligent Decision Support Systems A Journey to Smarter Healthcare

Intelligent Decision Support Systems   A Journey to Smarter Healthcare
Author: Smaranda Belciug,Florin Gorunescu
Publsiher: Springer
Total Pages: 271
Release: 2019-03-20
ISBN 10: 3030143546
ISBN 13: 9783030143541
Language: EN, FR, DE, ES & NL

Intelligent Decision Support Systems A Journey to Smarter Healthcare Book Review:

The goal of this book is to provide, in a friendly and refreshing manner, both theoretical concepts and practical techniques for the important and exciting field of Artificial Intelligence that can be directly applied to real-world healthcare problems. Healthcare – the final frontier. Lately, it seems like Pandora opened the box and evil was released into the world. Fortunately, there was one thing left in the box: hope. In recent decades, hope has been increasingly represented by Intelligent Decision Support Systems. Their continuing mission: to explore strange new diseases, to seek out new treatments and drugs, and to intelligently manage healthcare resources and patients. Hence, this book is designed for all those who wish to learn how to explore, analyze and find new solutions for the most challenging domain of all time: healthcare.

The Executive Guide to Artificial Intelligence

The Executive Guide to Artificial Intelligence
Author: Andrew Burgess
Publsiher: Springer
Total Pages: 181
Release: 2017-11-15
ISBN 10: 3319638203
ISBN 13: 9783319638201
Language: EN, FR, DE, ES & NL

The Executive Guide to Artificial Intelligence Book Review:

This book takes a pragmatic and hype–free approach to explaining artificial intelligence and how it can be utilised by businesses today. At the core of the book is a framework, developed by the author, which describes in non–technical language the eight core capabilities of Artificial Intelligence (AI). Each of these capabilities, ranging from image recognition, through natural language processing, to prediction, is explained using real–life examples and how they can be applied in a business environment. It will include interviews with executives who have successfully implemented AI as well as CEOs from AI vendors and consultancies. AI is one of the most talked about technologies in business today. It has the ability to deliver step–change benefits to organisations and enables forward–thinking CEOs to rethink their business models or create completely new businesses. But most of the real value of AI is hidden behind marketing hyperbole, confusing terminology, inflated expectations and dire warnings of ‘robot overlords’. Any business executive that wants to know how to exploit AI in their business today is left confused and frustrated. As an advisor in Artificial Intelligence, Andrew Burgess regularly comes face–to–face with business executives who are struggling to cut through the hype that surrounds AI. The knowledge and experience he has gained in advising them, as well as working as a strategic advisor to AI vendors and consultancies, has provided him with the skills to help business executives understand what AI is and how they can exploit its many benefits. Through the distilled knowledge included in this book business leaders will be able to take full advantage of this most disruptive of technologies and create substantial competitive advantage for their companies.

Advances in Integrated Energy Systems Design Control and Optimization

Advances in Integrated Energy Systems Design  Control and Optimization
Author: Josep M. Guerrero,Amjad Anvari-Moghaddam
Publsiher: MDPI
Total Pages: 184
Release: 2018-03-23
ISBN 10: 3038424900
ISBN 13: 9783038424901
Language: EN, FR, DE, ES & NL

Advances in Integrated Energy Systems Design Control and Optimization Book Review:

This book is a printed edition of the Special Issue "Advances in Integrated Energy Systems Design, Control and Optimization" that was published in Applied Sciences

Briggs

Briggs
Author: Barry Briggs,Eduardo Kassner
Publsiher: Microsoft Press
Total Pages: 112
Release: 2016-01-07
ISBN 10: 1509301992
ISBN 13: 9781509301997
Language: EN, FR, DE, ES & NL

Briggs Book Review:

How do you start? How should you build a plan for cloud migration for your entire portfolio? How will your organization be affected by these changes? This book, based on real-world cloud experiences by enterprise IT teams, seeks to provide the answers to these questions. Here, you’ll see what makes the cloud so compelling to enterprises; with which applications you should start your cloud journey; how your organization will change, and how skill sets will evolve; how to measure progress; how to think about security, compliance, and business buy-in; and how to exploit the ever-growing feature set that the cloud offers to gain strategic and competitive advantage.

Practical Machine Learning with Python

Practical Machine Learning with Python
Author: Dipanjan Sarkar,Raghav Bali,Tushar Sharma
Publsiher: Apress
Total Pages: 530
Release: 2017-12-20
ISBN 10: 1484232070
ISBN 13: 9781484232071
Language: EN, FR, DE, ES & NL

Practical Machine Learning with Python Book Review:

Master the essential skills needed to recognize and solve complex problems with machine learning and deep learning. Using real-world examples that leverage the popular Python machine learning ecosystem, this book is your perfect companion for learning the art and science of machine learning to become a successful practitioner. The concepts, techniques, tools, frameworks, and methodologies used in this book will teach you how to think, design, build, and execute machine learning systems and projects successfully. Practical Machine Learning with Python follows a structured and comprehensive three-tiered approach packed with hands-on examples and code. Part 1 focuses on understanding machine learning concepts and tools. This includes machine learning basics with a broad overview of algorithms, techniques, concepts and applications, followed by a tour of the entire Python machine learning ecosystem. Brief guides for useful machine learning tools, libraries and frameworks are also covered. Part 2 details standard machine learning pipelines, with an emphasis on data processing analysis, feature engineering, and modeling. You will learn how to process, wrangle, summarize and visualize data in its various forms. Feature engineering and selection methodologies will be covered in detail with real-world datasets followed by model building, tuning, interpretation and deployment. Part 3 explores multiple real-world case studies spanning diverse domains and industries like retail, transportation, movies, music, marketing, computer vision and finance. For each case study, you will learn the application of various machine learning techniques and methods. The hands-on examples will help you become familiar with state-of-the-art machine learning tools and techniques and understand what algorithms are best suited for any problem. Practical Machine Learning with Python will empower you to start solving your own problems with machine learning today! What You'll Learn Execute end-to-end machine learning projects and systems Implement hands-on examples with industry standard, open source, robust machine learning tools and frameworks Review case studies depicting applications of machine learning and deep learning on diverse domains and industries Apply a wide range of machine learning models including regression, classification, and clustering. Understand and apply the latest models and methodologies from deep learning including CNNs, RNNs, LSTMs and transfer learning. Who This Book Is For IT professionals, analysts, developers, data scientists, engineers, graduate students