Handbook of Artificial Intelligence Techniques in Photovoltaic Systems

Handbook of Artificial Intelligence Techniques in Photovoltaic Systems
Author: Soteris Kalogirou,Adel Mellit
Publsiher: Academic Press
Total Pages: 300
Release: 2022-06-01
ISBN 10: 012820642X
ISBN 13: 9780128206423
Language: EN, FR, DE, ES & NL

Handbook of Artificial Intelligence Techniques in Photovoltaic Systems Book Review:

Handbook of Artificial Intelligence Techniques in Photovoltaic Systems: Modelling, Control, Optimization, Forecasting and Fault Diagnosis provides readers with a comprehensive and detailed overview of the role of artificial intelligence in PV systems. Covering up-to-date research and methods on how, when and why to use and apply AI techniques in solving most photovoltaic problems, this book will serve as a complete reference in applying intelligent techniques and algorithms to increase PV system efficiency. Sections cover problem-solving data for challenges, including optimization, advanced control, output power forecasting, fault detection identification and localization, and more. Supported by the use of MATLAB and Simulink examples, this comprehensive illustration of AI-techniques and their applications in photovoltaic systems will provide valuable guidance for scientists and researchers working in this area. Includes intelligent methods in real-time using reconfigurable circuits FPGAs, DSPs and MCs Discusses the newest trends in AI forecasting, optimization and control applications Features MATLAB and Simulink examples highlighted throughout

Photovoltaic Systems

Photovoltaic Systems
Author: Taylor & Francis Group
Publsiher: CRC Press
Total Pages: 160
Release: 2022-03-07
ISBN 10: 9781032064260
ISBN 13: 1032064269
Language: EN, FR, DE, ES & NL

Photovoltaic Systems Book Review:

This book gives comprehensive insight to the fault detection techniques implemented for photovoltaic panels including predictive maintenance needed to improve the performance of solar PV systems using Artificial Intelligence techniques. It explains fault identification algorithms and their significance in real-time power system applications.

Introduction to AI Techniques for Renewable Energy System

Introduction to AI Techniques for Renewable Energy System
Author: Suman Lata Tripathi,Mithilesh Kumar Dubey,Vinay Rishiwal,Sanjeevikumar Padmanaban
Publsiher: CRC Press
Total Pages: 432
Release: 2021-11-24
ISBN 10: 1000392457
ISBN 13: 9781000392456
Language: EN, FR, DE, ES & NL

Introduction to AI Techniques for Renewable Energy System Book Review:

Introduction to AI techniques for Renewable Energy System Artificial Intelligence (AI) techniques play an essential role in modeling, analysis, and prediction of the performance and control of renewable energy. The algorithms used to model, control, or predict performances of the energy systems are complicated, involving differential equations, enormous computing power, and time requirements. Instead of complex rules and mathematical routines, AI techniques can learn critical information patterns within a multidimensional information domain. Design, control, and operation of renewable energy systems require a long-term series of meteorological data such as solar radiation, temperature, or wind data. Such long-term measurements are often non-existent for most of the interest locations or, wherever they are available, they suffer from several shortcomings, like inferior quality of data, and in-sufficient long series. The book focuses on AI techniques to overcome these problems. It summarizes commonly used AI methodologies in renewal energy, with a particular emphasis on neural networks, fuzzy logic, and genetic algorithms. It outlines selected AI applications for renewable energy. In particular, it discusses methods using the AI approach for prediction and modeling of solar radiation, seizing, performances, and controls of the solar photovoltaic (PV) systems. Features Focuses on a significant area of concern to develop a foundation for the implementation of renewable energy system with intelligent techniques Showcases how researchers working on renewable energy systems can correlate their work with intelligent and machine learning approaches Highlights international standards for intelligent renewable energy systems design, reliability, and maintenance Provides insights on solar cell, biofuels, wind, and other renewable energy systems design and characterization, including the equipment for smart energy systems This book, which includes real-life examples, is aimed at undergraduate and graduate students and academicians studying AI techniques used in renewal energy systems.

AI and IOT in Renewable Energy

AI and IOT in Renewable Energy
Author: Rabindra Nath Shaw,Nishad Mendis,Saad Mekhilef,Ankush Ghosh
Publsiher: Springer Nature
Total Pages: 109
Release: 2021-05-12
ISBN 10: 9811610118
ISBN 13: 9789811610110
Language: EN, FR, DE, ES & NL

AI and IOT in Renewable Energy Book Review:

This book presents the latest research on applications of artificial intelligence and the Internet of Things in renewable energy systems. Advanced renewable energy systems must necessarily involve the latest technology like artificial intelligence and Internet of Things to develop low cost, smart and efficient solutions. Intelligence allows the system to optimize the power, thereby making it a power efficient system; whereas, Internet of Things makes the system independent of wire and flexibility in operation. As a result, intelligent and IOT paradigms are finding increasing applications in the study of renewable energy systems. This book presents advanced applications of artificial intelligence and the internet of things in renewable energy systems development. It covers such topics as solar energy systems, electric vehicles etc. In all these areas applications of artificial intelligence methods such as artificial neural networks, genetic algorithms, fuzzy logic and a combination of the above, called hybrid systems, are included. The book is intended for a wide audience ranging from the undergraduate level up to the research academic and industrial communities engaged in the study and performance prediction of renewable energy systems.

Handbook of Research on Smart Technology Models for Business and Industry

Handbook of Research on Smart Technology Models for Business and Industry
Author: Thomas, J. Joshua,Fiore, Ugo,Lechuga, Gilberto Perez,Kharchenko, Valeriy,Vasant, Pandian
Publsiher: IGI Global
Total Pages: 491
Release: 2020-06-19
ISBN 10: 1799836460
ISBN 13: 9781799836469
Language: EN, FR, DE, ES & NL

Handbook of Research on Smart Technology Models for Business and Industry Book Review:

Advances in machine learning techniques and ever-increasing computing power has helped create a new generation of hardware and software technologies with practical applications for nearly every industry. As the progress has, in turn, excited the interest of venture investors, technology firms, and a growing number of clients, implementing intelligent automation in both physical and information systems has become a must in business. Handbook of Research on Smart Technology Models for Business and Industry is an essential reference source that discusses relevant abstract frameworks and the latest experimental research findings in theory, mathematical models, software applications, and prototypes in the area of smart technologies. Featuring research on topics such as digital security, renewable energy, and intelligence management, this book is ideally designed for machine learning specialists, industrial experts, data scientists, researchers, academicians, students, and business professionals seeking coverage on current smart technology models.

A Practical Guide for Advanced Methods in Solar Photovoltaic Systems

A Practical Guide for Advanced Methods in Solar Photovoltaic Systems
Author: Adel Mellit,Mohamed Benghanem
Publsiher: Springer Nature
Total Pages: 271
Release: 2020-05-27
ISBN 10: 3030434737
ISBN 13: 9783030434731
Language: EN, FR, DE, ES & NL

A Practical Guide for Advanced Methods in Solar Photovoltaic Systems Book Review:

The present book focuses on recent advances methods and applications in photovoltaic (PV) systems. The book is divided into two parts: the first part deals with some theoretical, simulation and experiments on solar cells, including efficiency improvement, new materials and behavior performances. While the second part of the book devoted mainly on the application of advanced methods in PV systems, including advanced control, FPGA implementation, output power forecasting based artificial intelligence technique (AI), high PV penetration, reconfigurable PV architectures and fault detection and diagnosis based AI. The authors of the book trying to show to readers more details about some theoretical methods and applications in solar cells and PV systems (eg. advanced algorithms for control, optimization, power forecasting, monitoring and fault diagnosis methods). The applications are mainly carried out in different laboratories and location around the world as projects (Algeria, KSA, Turkey, Morocco, Italy and France). The book will be addressed to scientists, academics, researchers and PhD students working in this topic. The book will help readers to understand some applications including control, forecasting, monitoring, fault diagnosis of photovoltaic plants, as well as in solar cells such as behavior performances and efficiency improvement. It could be also be used as a reference and help industry sectors interested by prototype development.

Handbook of Research on Solar Energy Systems and Technologies

Handbook of Research on Solar Energy Systems and Technologies
Author: Anwar, Sohail
Publsiher: IGI Global
Total Pages: 614
Release: 2012-08-31
ISBN 10: 146661997X
ISBN 13: 9781466619975
Language: EN, FR, DE, ES & NL

Handbook of Research on Solar Energy Systems and Technologies Book Review:

The last ten years have seen rapid advances in nanoscience and nanotechnology, allowing unprecedented manipulation of the nanoscale structures controlling solar capture, conversion, and storage. Filled with cutting-edge solar energy research and reference materials, the Handbook of Research on Solar Energy Systems and Technologies serves as a one-stop resource for the latest information regarding different topical areas within solar energy. This handbook will emphasize the application of nanotechnology innovations to solar energy technologies, explore current and future developments in third generation solar cells, and provide a detailed economic analysis of solar energy applications.

Intelligent Renewable Energy Systems

Intelligent Renewable Energy Systems
Author: Neeraj Priyadarshi,Akash Kumar Bhoi,Sanjeevikumar Padmanaban,S. Balamurugan,Jens Bo Holm-Nielsen
Publsiher: John Wiley & Sons
Total Pages: 480
Release: 2021-12-29
ISBN 10: 1119786282
ISBN 13: 9781119786283
Language: EN, FR, DE, ES & NL

Intelligent Renewable Energy Systems Book Review:

INTELLIGENT RENEWABLE ENERGY SYSTEMS This collection of papers on artificial intelligence and other methods for improving renewable energy systems, written by industry experts, is a reflection of the state of the art, a must-have for engineers, maintenance personnel, students, and anyone else wanting to stay abreast with current energy systems concepts and technology. Renewable energy is one of the most important subjects being studied, researched, and advanced in today’s world. From a macro level, like the stabilization of the entire world’s economy, to the micro level, like how you are going to heat or cool your home tonight, energy, specifically renewable energy, is on the forefront of the discussion. This book illustrates modelling, simulation, design and control of renewable energy systems employed with recent artificial intelligence (AI) and optimization techniques for performance enhancement. Current renewable energy sources have less power conversion efficiency because of its intermittent and fluctuating behavior. Therefore, in this regard, the recent AI and optimization techniques are able to deal with data ambiguity, noise, imprecision, and nonlinear behavior of renewable energy sources more efficiently compared to classical soft computing techniques. This book provides an extensive analysis of recent state of the art AI and optimization techniques applied to green energy systems. Subsequently, researchers, industry persons, undergraduate and graduate students involved in green energy will greatly benefit from this comprehensive volume, a must-have for any library. Audience Engineers, scientists, managers, researchers, students, and other professionals working in the field of renewable energy.

Photovoltaic Systems

Photovoltaic Systems
Author: K.Mohana Sundaram,Sanjeevikumar Padmanaban,Jens Bo Holm-Nielsen,P. Pandiyan
Publsiher: CRC Press
Total Pages: 150
Release: 2022-03-07
ISBN 10: 100054589X
ISBN 13: 9781000545890
Language: EN, FR, DE, ES & NL

Photovoltaic Systems Book Review:

This book provides comprehensive insight into the fault detection techniques implemented for photovoltaic (PV) panels. It includes studies related to predictive maintenance needed to improve the performance of the solar PV systems using Artificial Intelligence (AI) techniques. The readers gain knowledge on the fault identification algorithm and the significance of all such algorithms in real-time power system applications. Gives detailed overview of fundamental concepts of fault diagnosis algorithm for solar PV system Explains AC and DC side of the solar PV system-based electricity generation with real-time examples Covers effective extraction of the energy from solar radiation Illustrates artificial intelligence techniques for detecting the faults occurring in the solar PV system Includes MATLAB® based simulations and results on fault diagnosis including case studies This book is aimed at researchers, professionals and graduate students in electrical engineering, artificial intelligence, control algorithms, energy engineering, photovoltaic systems, industrial electronics.

Applied Soft Computing and Embedded System Applications in Solar Energy

Applied Soft Computing and Embedded System Applications in Solar Energy
Author: Rupendra Kumar Pachauri,Jitendra Kumar Pandey,Abhishek Sharmu,Om Prakash Nautiyal,Mangey Ram
Publsiher: CRC Press
Total Pages: 254
Release: 2021-05-27
ISBN 10: 1000391698
ISBN 13: 9781000391695
Language: EN, FR, DE, ES & NL

Applied Soft Computing and Embedded System Applications in Solar Energy Book Review:

Applied Soft Computing and Embedded System Applications in Solar Energy deals with energy systems and soft computing methods from a wide range of approaches and application perspectives. The authors examine how embedded system applications can deal with the smart monitoring and controlling of stand-alone and grid-connected solar photovoltaic (PV) systems for increased efficiency. Growth in the area of artificial intelligence with embedded system applications has led to a new era in computing, impacting almost all fields of science and engineering. Soft computing methods implemented to energy-related problems regularly face data-driven issues such as problems of optimization, classification, clustering, or prediction. The authors offer real-time implementation of soft computing and embedded system in the area of solar energy to address the issues with microgrid and smart grid projects (both renewable and non-renewable generations), energy management, and power regulation. They also discuss and examine alternative solutions for energy capacity assessment, energy efficiency systems design, as well as other specific smart grid energy system applications. The book is intended for students, professionals, and researchers in electrical and computer engineering fields, working on renewable energy resources, microgrids, and smart grid projects. Examines the integration of hardware with stand-alone PV panels and real-time monitoring of factors affecting the efficiency of the PV panels Offers real-time implementation of soft computing and embedded system in the area of solar energy Discusses how soft computing plays a huge role in the prediction of efficiency of stand-alone and grid-connected solar PV systems Discusses how embedded system applications with smart monitoring can control and enhance the efficiency of stand-alone and grid-connected solar PV systems Explores swarm intelligence techniques for solar PV parameter estimation Dr. Rupendra Kumar Pachauri is Assistant Professor - Selection Grade in the Department of Electrical and Electronics Engineering, University of Petroleum and Energy Studies (UPES), Dehradun, India. Dr. Jitendra Kumar Pandey is Professor & Head of R&D in the University of Petroleum and Energy Studies (UPES), Dehradun, India. Mr. Abhishek Sharma is working as a research scientist in the research and development department (UPES, India). Dr. Om Prakash Nautiyal is working as a scientist in Uttarakhand Science Education & Research Centre (USERC), Department of Information and Science Technology, Govt. of Uttarakhand, Dehradun, India. Prof. Mangey Ram is working as a Research Professor at Graphic Era Deemed to be University, Dehradun, India.

AI and Machine Learning Paradigms for Health Monitoring System

AI and Machine Learning Paradigms for Health Monitoring System
Author: Hasmat Malik,Nuzhat Fatema,Jafar A. Alzubi
Publsiher: Springer Nature
Total Pages: 513
Release: 2021-02-14
ISBN 10: 9813344121
ISBN 13: 9789813344129
Language: EN, FR, DE, ES & NL

AI and Machine Learning Paradigms for Health Monitoring System Book Review:

This book embodies principles and applications of advanced soft computing approaches in engineering, healthcare and allied domains directed toward the researchers aspiring to learn and apply intelligent data analytics techniques. The first part covers AI, machine learning and data analytics tools and techniques and their applications to the class of several hospital and health real-life problems. In the later part, the applications of AI, ML and data analytics shall be covered over the wide variety of applications in hospital, health, engineering and/or applied sciences such as the clinical services, medical image analysis, management support, quality analysis, bioinformatics, device analysis and operations. The book presents knowledge of experts in the form of chapters with the objective to introduce the theme of intelligent data analytics and discusses associated theoretical applications. At last, it presents simulation codes for the problems included in the book for better understanding for beginners.

Handbook Of Green Materials Processing Technologies Properties And Applications In 4 Volumes

Handbook Of Green Materials  Processing Technologies  Properties And Applications  In 4 Volumes
Author: Oksman Kristiina,Mathew Aji P,Bismarck Alexander
Publsiher: World Scientific
Total Pages: 1124
Release: 2014-04-11
ISBN 10: 9814566470
ISBN 13: 9789814566476
Language: EN, FR, DE, ES & NL

Handbook Of Green Materials Processing Technologies Properties And Applications In 4 Volumes Book Review:

Green materials and green nanotechnology have gained widespread interest over the last 15 years; first in academia, then in related industries in the last few years.The Handbook of Green Materials serves as reference literature for undergraduates and graduates studying materials science and engineering, composite materials, chemical engineering, bioengineering and materials physics; and for researchers, professional engineers and consultants from polymer or forest industries who encounter biobased nanomaterials, bionanocomposites, self- and direct-assembled nanostructures and green composite materials in their lines of work.This four-volume set contains material ranging from basic, background information on the fields discussed, to reports on the latest research and industrial activities, and finally the works by contributing authors who are prominent experts of the subjects they address in this set.The four volumes comprise of:The first volume explains the structure of cellulose; different sources of raw material; the isolation/separation processes of nanomaterials from different material sources; and properties and characteristics of cellulose nanofibers and nanocrystals (starch nanomaterials). Information on the different characterization methods and the most important properties of biobased nanomaterials are also covered. The industrial point of view regarding both the processability and access of these nanomaterials, as well as large scale manufacturing and their industrial application is discussed — particularly in relation to the case of the paper industry.The second volume expounds on different bionanocomposites based on cellulose nanofibers or nanocrystals and their preparation/manufacturing processes. It also provides information on different characterization methods and the most important properties of bionanocomposites, as well as techniques of modeling the mechanical properties of nanocomposites. This volume presents the industrial point of view regarding large scale manufacturing and their applications from the perspective of their medical uses in printed electronics and in adhesives.The third volume deals with the ability of bionanomaterials to self-assemble in either liquids or forming organized solid materials. The chemistry of cellulose nanomaterials and chemical modifications as well as different assembling techniques and used characterization methods, and the most important properties which can be achieved by self-assembly, are described. The chapters, for example, discuss subjects such as ultra-light biobased aerogels based on cellulose and chitin, thin films suitable as barrier layers, self-sensing nanomaterials, and membranes for water purification.The fourth volume reviews green composite materials — including green raw materials — such as biobased carbon fibers, regenerated cellulose fibers and thermoplastic and thermoset polymers (e.g. PLA, bio-based polyolefines, polysaccharide polymers, natural rubber, bio-based polyurethane, lignin polymer, and furfurylalchohol). The most important composite processing technologies are described, including: prepregs of green composites, compounding, liquid composite molding, foaming, and compression molding. Industrial applications, especially for green transportation and the electronics industry, are also described.This four-volume set is a must-have for anyone keen to acquire knowledge on novel bionanomaterials — including structure-property correlations, isolation and purification processes of nanofibers and nanocrystals, their important characteristics, processing technologies, industrial up-scaling and suitable industry applications. The handbook is a useful reference not only for teaching activities but also for researchers who are working in this field.

Handbook of Research on Manufacturing Process Modeling and Optimization Strategies

Handbook of Research on Manufacturing Process Modeling and Optimization Strategies
Author: Das, Raja,Pradhan, Mohan
Publsiher: IGI Global
Total Pages: 530
Release: 2017-03-10
ISBN 10: 152252441X
ISBN 13: 9781522524410
Language: EN, FR, DE, ES & NL

Handbook of Research on Manufacturing Process Modeling and Optimization Strategies Book Review:

Recent improvements in business process strategies have allowed more opportunities to attain greater developmental performances. This has led to higher success in day-to-day production and overall competitive advantage. The Handbook of Research on Manufacturing Process Modeling and Optimization Strategies is a pivotal reference source for the latest research on the various manufacturing methodologies and highlights the best optimization approaches to achieve boosted process performance. Featuring extensive coverage on relevant areas such as genetic algorithms, fuzzy set theory, and soft computing techniques, this publication is an ideal resource for researchers, practitioners, academicians, designers, manufacturing engineers, and institutions involved in design and manufacturing projects.

Solar Photovoltaic Power Plants

Solar Photovoltaic Power Plants
Author: Radu-Emil Precup,Tariq Kamal,Syed Zulqadar Hassan
Publsiher: Springer
Total Pages: 250
Release: 2019-02-07
ISBN 10: 9811361517
ISBN 13: 9789811361517
Language: EN, FR, DE, ES & NL

Solar Photovoltaic Power Plants Book Review:

This book discusses control and optimization techniques in the broadest sense, covering new theoretical results and the applications of newly developed methods for PV systems. Going beyond classical control techniques, it promotes the use of more efficient control and optimization strategies based on linearized models and purely continuous (or discrete) models. These new strategies not only enhance the performance of the PV systems, but also decrease the cost per kilowatt-hour generated.

Multimodal Biometrics and Intelligent Image Processing for Security Systems

Multimodal Biometrics and Intelligent Image Processing for Security Systems
Author: Marina L. Gavrilova,Maruf Monwar
Publsiher: IGI Global
Total Pages: 326
Release: 2013-03-31
ISBN 10: 1466636475
ISBN 13: 9781466636477
Language: EN, FR, DE, ES & NL

Multimodal Biometrics and Intelligent Image Processing for Security Systems Book Review:

"This book provides an in-depth description of existing and fresh fusion approaches for multimodal biometric systems, covering relevant topics affecting the security and intelligent industries"--Provided by publisher.

Handbook of Clean Energy Systems 6 Volume Set

Handbook of Clean Energy Systems  6 Volume Set
Author: Jinyue Yan
Publsiher: John Wiley & Sons
Total Pages: 4032
Release: 2015-06-22
ISBN 10: 1118388585
ISBN 13: 9781118388587
Language: EN, FR, DE, ES & NL

Handbook of Clean Energy Systems 6 Volume Set Book Review:

The Handbook of Clean Energy Systems brings together an international team of experts to present a comprehensive overview of the latest research, developments and practical applications throughout all areas of clean energy systems. Consolidating information which is currently scattered across a wide variety of literature sources, the handbook covers a broad range of topics in this interdisciplinary research field including both fossil and renewable energy systems. The development of intelligent energy systems for efficient energy processes and mitigation technologies for the reduction of environmental pollutants is explored in depth, and environmental, social and economic impacts are also addressed. Topics covered include: Volume 1 - Renewable Energy: Biomass resources and biofuel production; Bioenergy Utilization; Solar Energy; Wind Energy; Geothermal Energy; Tidal Energy. Volume 2 - Clean Energy Conversion Technologies: Steam/Vapor Power Generation; Gas Turbines Power Generation; Reciprocating Engines; Fuel Cells; Cogeneration and Polygeneration. Volume 3 - Mitigation Technologies: Carbon Capture; Negative Emissions System; Carbon Transportation; Carbon Storage; Emission Mitigation Technologies; Efficiency Improvements and Waste Management; Waste to Energy. Volume 4 - Intelligent Energy Systems: Future Electricity Markets; Diagnostic and Control of Energy Systems; New Electric Transmission Systems; Smart Grid and Modern Electrical Systems; Energy Efficiency of Municipal Energy Systems; Energy Efficiency of Industrial Energy Systems; Consumer Behaviors; Load Control and Management; Electric Car and Hybrid Car; Energy Efficiency Improvement. Volume 5 - Energy Storage: Thermal Energy Storage; Chemical Storage; Mechanical Storage; Electrochemical Storage; Integrated Storage Systems. Volume 6 - Sustainability of Energy Systems: Sustainability Indicators, Evaluation Criteria, and Reporting; Regulation and Policy; Finance and Investment; Emission Trading; Modeling and Analysis of Energy Systems; Energy vs. Development; Low Carbon Economy; Energy Efficiencies and Emission Reduction. Key features: Comprising over 3,500 pages in 6 volumes, HCES presents a comprehensive overview of the latest research, developments and practical applications throughout all areas of clean energy systems, consolidating a wealth of information which is currently scattered across a wide variety of literature sources. In addition to renewable energy systems, HCES also covers processes for the efficient and clean conversion of traditional fuels such as coal, oil and gas, energy storage systems, mitigation technologies for the reduction of environmental pollutants, and the development of intelligent energy systems. Environmental, social and economic impacts of energy systems are also addressed in depth. Published in full colour throughout. Fully indexed with cross referencing within and between all six volumes. Edited by leading researchers from academia and industry who are internationally renowned and active in their respective fields. Published in print and online. The online version is a single publication (i.e. no updates), available for one-time purchase or through annual subscription.

Artificial Intelligence in Energy and Renewable Energy Systems

Artificial Intelligence in Energy and Renewable Energy Systems
Author: Soteris Kalogirou
Publsiher: Nova Publishers
Total Pages: 471
Release: 2007
ISBN 10: 9781600212611
ISBN 13: 1600212611
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Energy and Renewable Energy Systems Book Review:

This book presents state of the art applications of artificial intelligence in energy and renewable energy systems design and modelling. It covers such topics as solar energy, wind energy, biomass and hydrogen as well as building services systems, power generation systems, combustion processes and refrigeration. In all these areas applications of artificial intelligence methods such as artificial neural networks, genetic algorithms, fuzzy logic and a combination of the above, called hybrid systems, are included. The book is intended for a wide audience ranging from the undergraduate level up to the research academic and industrial communities dealing with modelling and performance prediction of energy and renewable energy systems.

Artificial Intelligence for Renewable Energy Systems

Artificial Intelligence for Renewable Energy Systems
Author: Ajay Kumar Vyas,S. Balamurugan,Kamal Kant Hiran,Harsh S. Dhiman
Publsiher: John Wiley & Sons
Total Pages: 272
Release: 2022-01-28
ISBN 10: 1119761719
ISBN 13: 9781119761716
Language: EN, FR, DE, ES & NL

Artificial Intelligence for Renewable Energy Systems Book Review:

ARTIFICIAL INTELLIGENCE FOR RENEWABLE ENERGY SYSTEMS Renewable energy systems, including solar, wind, biodiesel, hybrid energy, and other relevant types, have numerous advantages compared to their conventional counterparts. This book presents the application of machine learning and deep learning techniques for renewable energy system modeling, forecasting, and optimization for efficient system design. Due to the importance of renewable energy in today’s world, this book was designed to enhance the reader’s knowledge based on current developments in the field. For instance, the extraction and selection of machine learning algorithms for renewable energy systems, forecasting of wind and solar radiation are featured in the book. Also highlighted are intelligent data, renewable energy informatics systems based on supervisory control and data acquisition (SCADA); and intelligent condition monitoring of solar and wind energy systems. Moreover, an AI-based system for real-time decision-making for renewable energy systems is presented; and also demonstrated is the prediction of energy consumption in green buildings using machine learning. The chapter authors also provide both experimental and real datasets with great potential in the renewable energy sector, which apply machine learning (ML) and deep learning (DL) algorithms that will be helpful for economic and environmental forecasting of the renewable energy business. Audience The primary target audience includes research scholars, industry engineers, and graduate students working in renewable energy, electrical engineering, machine learning, information & communication technology.

Intelligent Information Systems and Knowledge Management for Energy Applications for Decision Support Usage and Environmental Protection

Intelligent Information Systems and Knowledge Management for Energy  Applications for Decision Support  Usage  and Environmental Protection
Author: Metaxiotis, Kostas
Publsiher: IGI Global
Total Pages: 524
Release: 2009-08-31
ISBN 10: 1605667382
ISBN 13: 9781605667386
Language: EN, FR, DE, ES & NL

Intelligent Information Systems and Knowledge Management for Energy Applications for Decision Support Usage and Environmental Protection Book Review:

"This book analyzes the need for a holistic approach for the construction and engineering of cities and societies"--Provided by publisher.

Artificial Intelligence Techniques for Rational Decision Making

Artificial Intelligence Techniques for Rational Decision Making
Author: Tshilidzi Marwala
Publsiher: Springer
Total Pages: 168
Release: 2014-10-20
ISBN 10: 3319114247
ISBN 13: 9783319114248
Language: EN, FR, DE, ES & NL

Artificial Intelligence Techniques for Rational Decision Making Book Review:

Develops insights into solving complex problems in engineering, biomedical sciences, social science and economics based on artificial intelligence. Some of the problems studied are in interstate conflict, credit scoring, breast cancer diagnosis, condition monitoring, wine testing, image processing and optical character recognition. The author discusses and applies the concept of flexibly-bounded rationality which prescribes that the bounds in Nobel Laureate Herbert Simon’s bounded rationality theory are flexible due to advanced signal processing techniques, Moore’s Law and artificial intelligence. Artificial Intelligence Techniques for Rational Decision Making examines and defines the concepts of causal and correlation machines and applies the transmission theory of causality as a defining factor that distinguishes causality from correlation. It develops the theory of rational counterfactuals which are defined as counterfactuals that are intended to maximize the attainment of a particular goal within the context of a bounded rational decision making process. Furthermore, it studies four methods for dealing with irrelevant information in decision making: Theory of the marginalization of irrelevant information Principal component analysis Independent component analysis Automatic relevance determination method In addition it studies the concept of group decision making and various ways of effecting group decision making within the context of artificial intelligence. Rich in methods of artificial intelligence including rough sets, neural networks, support vector machines, genetic algorithms, particle swarm optimization, simulated annealing, incremental learning and fuzzy networks, this book will be welcomed by researchers and students working in these areas.