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Advanced Machine Learning Technologies and Applications: Proceedings of AMLTA 2020 (Advances in Intelligent Systems and Computing #1141)
by Aboul Ella Hassanien Roheet Bhatnagar Ashraf DarwishThis book presents the refereed proceedings of the 5th International Conference on Advanced Machine Learning Technologies and Applications (AMLTA 2020), held at Manipal University Jaipur, India, on February 13 – 15, 2019, and organized in collaboration with the Scientific Research Group in Egypt (SRGE). The papers cover current research in machine learning, big data, Internet of Things, biomedical engineering, fuzzy logic and security, as well as intelligence swarms and optimization.
Advanced Machine Learning Technologies and Applications: Proceedings of AMLTA 2021 (Advances in Intelligent Systems and Computing #1339)
by Aboul-Ella Hassanien Kuo-Chi Chang Tang MincongThis book presents the refereed proceedings of the 6th International Conference on Advanced Machine Learning Technologies and Applications (AMLTA 2021) held in Cairo, Egypt, during March 22–24, 2021, and organized by the Scientific Research Group of Egypt (SRGE). The papers cover current research Artificial Intelligence Against COVID-19, Internet of Things Healthcare Systems, Deep Learning Technology, Sentiment analysis, Cyber-Physical System, Health Informatics, Data Mining, Power and Control Systems, Business Intelligence, Social media, Control Design, and Smart Systems.
Advanced Machine Learning with Evolutionary and Metaheuristic Techniques (Computational Intelligence Methods and Applications)
by Jayaraman Valadi Krishna Pratap Singh Muneendra Ojha Patrick SiarryThis book delves into practical implementation of evolutionary and metaheuristic algorithms to advance the capacity of machine learning. The readers can gain insight into the capabilities of data-driven evolutionary optimization in materials mechanics, and optimize your learning algorithms for maximum efficiency. Or unlock the strategies behind hyperparameter optimization to enhance your transfer learning algorithms, yielding remarkable outcomes. Or embark on an illuminating journey through evolutionary techniques designed for constructing deep-learning frameworks. The book also introduces an intelligent RPL attack detection system tailored for IoT networks. Explore a promising avenue of optimization by fusing Particle Swarm Optimization with Reinforcement Learning. It uncovers the indispensable role of metaheuristics in supervised machine learning algorithms. Ultimately, this book bridges the realms of evolutionary dynamic optimization andmachine learning, paving the way for pioneering innovations in the field.
Advanced Machine Learning with Python
by John HeartySolve challenging data science problems by mastering cutting-edge machine learning techniques in Python About This Book * Resolve complex machine learning problems and explore deep learning * Learn to use Python code for implementing a range of machine learning algorithms and techniques * A practical tutorial that tackles real-world computing problems through a rigorous and effective approach Who This Book Is For This title is for Python developers and analysts or data scientists who are looking to add to their existing skills by accessing some of the most powerful recent trends in data science. If you've ever considered building your own image or text-tagging solution, or of entering a Kaggle contest for instance, this book is for you! Prior experience of Python and grounding in some of the core concepts of machine learning would be helpful. What You Will Learn * Compete with top data scientists by gaining a practical and theoretical understanding of cutting-edge deep learning algorithms * Apply your new found skills to solve real problems, through clearly-explained code for every technique and test * Automate large sets of complex data and overcome time-consuming practical challenges * Improve the accuracy of models and your existing input data using powerful feature engineering techniques * Use multiple learning techniques together to improve the consistency of results * Understand the hidden structure of datasets using a range of unsupervised techniques * Gain insight into how the experts solve challenging data problems with an effective, iterative, and validation-focused approach * Improve the effectiveness of your deep learning models further by using powerful ensembling techniques to strap multiple models together In Detail Designed to take you on a guided tour of the most relevant and powerful machine learning techniques in use today by top data scientists, this book is just what you need to push your Python algorithms to maximum potential. Clear examples and detailed code samples demonstrate deep learning techniques, semi-supervised learning, and more - all whilst working with real-world applications that include image, music, text, and financial data. The machine learning techniques covered in this book are at the forefront of commercial practice. They are applicable now for the first time in contexts such as image recognition, NLP and web search, computational creativity, and commercial/financial data modeling. Deep Learning algorithms and ensembles of models are in use by data scientists at top tech and digital companies, but the skills needed to apply them successfully, while in high demand, are still scarce. This book is designed to take the reader on a guided tour of the most relevant and powerful machine learning techniques. Clear descriptions of how techniques work and detailed code examples demonstrate deep learning techniques, semi-supervised learning and more, in real world applications. We will also learn about NumPy and Theano. By this end of this book, you will learn a set of advanced Machine Learning techniques and acquire a broad set of powerful skills in the area of feature selection & feature engineering. Style and approach This book focuses on clarifying the theory and code behind complex algorithms to make them practical, useable, and well-understood. Each topic is described with real-world applications, providing both broad contextual coverage and detailed guidance.
Advanced Machine Learning with R: Tackle data analytics and machine learning challenges and build complex applications with R 3.5
by Cory Lesmeister Dr. Sunil ChinnamgariMaster machine learning techniques with real-world projects that interface TensorFlow with R, H2O, MXNet, and other languagesKey FeaturesGain expertise in machine learning, deep learning and other techniquesBuild intelligent end-to-end projects for finance, social media, and a variety of domainsImplement multi-class classification, regression, and clusteringBook DescriptionR is one of the most popular languages when it comes to exploring the mathematical side of machine learning and easily performing computational statistics.This Learning Path shows you how to leverage the R ecosystem to build efficient machine learning applications that carry out intelligent tasks within your organization. You'll tackle realistic projects such as building powerful machine learning models with ensembles to predict employee attrition. You'll explore different clustering techniques to segment customers using wholesale data and use TensorFlow and Keras-R for performing advanced computations. You’ll also be introduced to reinforcement learning along with its various use cases and models. Additionally, it shows you how some of these black-box models can be diagnosed and understood.By the end of this Learning Path, you’ll be equipped with the skills you need to deploy machine learning techniques in your own projects.This Learning Path includes content from the following Packt products:R Machine Learning Projects by Dr. Sunil Kumar ChinnamgariMastering Machine Learning with R - Third Edition by Cory LesmeisterWhat you will learnDevelop a joke recommendation engine to recommend jokes that match users’ tastesBuild autoencoders for credit card fraud detectionWork with image recognition and convolutional neural networksMake predictions for casino slot machine using reinforcement learningImplement NLP techniques for sentiment analysis and customer segmentationProduce simple and effective data visualizations for improved insightsUse NLP to extract insights for textImplement tree-based classifiers including random forest and boosted treeWho this book is forIf you are a data analyst, data scientist, or machine learning developer this is an ideal Learning Path for you. Each project will help you test your skills in implementing machine learning algorithms and techniques. A basic understanding of machine learning and working knowledge of R programming is necessary to get the most out of this Learning Path.
Advanced Maintenance Policies for Shock and Damage Models (Springer Series in Reliability Engineering)
by Toshio Nakagawa Xufeng ZhaoThis book surveys the recent development of maintenance theory, advanced maintenance techniques with shock and damage models, and their applications in computer systems dealing with efficiency problems. It also equips readers to handle multiple maintenance, informs maintenance policies, and explores comparative methods for several different kinds of maintenance. Further, it discusses shock and damage modelling as an important failure mechanism for reliability systems, and extensively explores the degradation processes, failure modes, and maintenance characteristics of modern, highly complex systems, especially for some key mechanical systems designed for specific tasks.
Advanced Manufacturing and Automation IX (Lecture Notes in Electrical Engineering #634)
by Yi Wang Kristian Martinsen Tao Yu Kesheng WangThis book presents selected papers from the 9th International Workshop of Advanced Manufacturing and Automation (IWAMA 2019), held in Plymouth, UK, on November 21–22, 2019. Discussing topics such as novel techniques for manufacturing and automation in Industry 4.0 and smart factories, which are vital for maintaining and improving economic development and quality of life, it offers researchers and industrial engineers insights into implementing the concepts and theories of Industry 4.0, in order to effectively respond to the challenges posed by the 4th industrial revolution and smart factories.
Advanced Manufacturing and Automation VIII (Lecture Notes in Electrical Engineering #484)
by Kesheng Wang Yi Wang Jan Ola Strandhagen Tao YuThis proceeding is a compilation of selected papers from the 8th International Workshop of Advanced Manufacturing and Automation (IWAMA 2018), held in Changzhou, China on September 25 - 26, 2018. Most of the topics are focusing on novel techniques for manufacturing and automation in Industry 4.0 and smart factory. These contributions are vital for maintaining and improving economic development and quality of life. The proceeding will assist academic researchers and industrial engineers to implement the concepts and theories of Industry 4.0 in industrial practice, in order to effectively respond to the challenges posed by the 4th industrial revolution and smart factory.
Advanced Manufacturing and Automation X (Lecture Notes in Electrical Engineering #737)
by Yi Wang Kesheng Wang Tao Yu Kristian MartinsenThis book presents selected papers from the 10th International Workshop of Advanced Manufacturing and Automation (IWAMA 2020), held in Zhanjiang, Guangdong province, China, on October 12-13, 2020. Discussing topics such as novel techniques for manufacturing and automation in Industry 4.0 and smart factories, which are vital for maintaining and improving economic development and quality of life, it offers researchers and industrial engineers insights into implementing the concepts and theories of Industry 4.0, in order to effectively respond to the challenges posed by the 4th industrial revolution and smart factories.
Advanced Manufacturing and Automation XI (Lecture Notes in Electrical Engineering #880)
by Yi Wang Kristian Martinsen Tao Yu Kesheng WangThe proceedings collect selected papers from the 11th International Workshop of Advanced Manufacturing and Automation (IWAMA 2021), held in Zhengzhou Polytechnic, China on 11 - 12 October, 2021. Topics focusing on novel techniques for manufacturing and automation in Industry 4.0 are now vital factors for the maintenance and improvement of the economy of a nation and the quality of life. It will help academic researchers and engineering to implement the concept, theory and methods in Industry 4.0 which has been a hot topic. These proceedings will make valuable contributions to academic researchers, engineers in the industry for the challenges in the 4th industry revolution and smart factories.
Advanced Manufacturing Processes: Selected Papers from the Grabchenko’s International Conference on Advanced Manufacturing Processes (InterPartner-2019), September 10-13, 2019, Odessa, Ukraine (Lecture Notes in Mechanical Engineering)
by Volodymyr Tonkonogyi Vitalii Ivanov Justyna Trojanowska Gennadii Oborskyi Milan Edl Ivan Kuric Ivan Pavlenko Predrag DasicThis book offers a timely yet comprehensive snapshot of innovative research and developments in the area of manufacturing. It covers a wide range of manufacturing processes, such as cutting, coatings, and grinding, highlighting the advantages provided by the use of new materials and composites, as well as new methods and technologies. It discusses topics in energy generation and pollution prevention. It shows how computational methods and mathematical models have been applied to solve a number of issues in both theoretical and applied research. Based on selected papers presented at the Grabchenko’s International Conference on Advanced Manufacturing Processes (InterPartner-2019), held in Odessa, Ukraine on September 10-13, 2019, this book offers a timely overview and extensive information on trends and technologies in the area of manufacturing, mechanical and materials engineering. It is also intended to facilitate communication and collaboration between different groups working on similar topics, and to offer a bridge between academic and industrial researchers.
Advanced Manufacturing Processes II: Selected Papers from the 2nd Grabchenko’s International Conference on Advanced Manufacturing Processes (InterPartner-2020), September 8-11, 2020, Odessa, Ukraine (Lecture Notes in Mechanical Engineering)
by Volodymyr Tonkonogyi Vitalii Ivanov Justyna Trojanowska Gennadii Oborskyi Anatolii Grabchenko Ivan Pavlenko Milan Edl Ivan Kuric Predrag DasicThis book offers a timely yet comprehensive snapshot of innovative research and developments at the interface between manufacturing, materials and mechanical engineering, and quality assurance. It covers a wide range of manufacturing processes, such as cutting, grinding, assembly, and coatings, including ultrasonic treatment, molding, radial-isostatic compression, ionic-plasma deposition, volumetric vibration treatment, and wear resistance. It also highlights the advantages of augmented reality, RFID technology, reverse engineering, optimization, heat and mass transfer, energy management, quality inspection, and environmental impact. Based on selected papers presented at the Grabchenko’s International Conference on Advanced Manufacturing Processes (InterPartner-2020), held in Odessa, Ukraine, on September 8–11, 2020, this book offers a timely overview and extensive information on trends and technologies in production planning, design engineering, advanced materials, machining processes, process engineering, and quality assurance. It is also intended to facilitate communication and collaboration between different groups working on similar topics and offer a bridge between academic and industrial researchers.
Advanced Manufacturing Processes III: Selected Papers from the 3rd Grabchenko’s International Conference on Advanced Manufacturing Processes (InterPartner-2021), September 7-10, 2021, Odessa, Ukraine (Lecture Notes in Mechanical Engineering)
by Volodymyr Tonkonogyi Vitalii Ivanov Justyna Trojanowska Gennadii Oborskyi Ivan PavlenkoThis book offers a timely snapshot of innovative research and developments at the interface between manufacturing, materials and mechanical engineering, and quality assurance. It covers a wide range of manufacturing processes, such as grinding, boring, milling, turning, woodworking, coatings, including additive manufacturing. It focuses on laser, ultrasonic, and combined laser–ultrasonic hardening treatments, and dispersion hardening. It describes tribology and functional analysis of coatings, separation, purification and filtration processes, as well as ecological recirculation and electrohydraulic activation, highlighting the growing role of digital twins, optimization and lifecycle management methods, and quality inspection processes. It also covers cutting-edge heat and mass transfer technologies and energy management methods. Gathering the best papers presented at the 3rd Grabchenko’s International Conference on Advanced Manufacturing Processes (InterPartner-2021), held in Odessa, Ukraine, on September 7–10, 2021, this book offers a timely overview and extensive information on trends and technologies in manufacturing, mechanical, and materials engineering, and quality assurance. It is also intended to facilitate communication and collaboration between different groups working on similar topics and to offer a bridge between academic and industrial researchers.
Advanced Materials Modelling for Structures: With Multi-scale Effects Or Under Multi-field Actions (Advanced Structured Materials #19)
by Holm Altenbach Serge KruchThis volume presents the major outcome of the IUTAM symposium on "Advanced Materials Modeling for Structures". It discusses advances in high temperature materials research, and also to provides a discussion the new horizon of this fundamental field of applied mechanics. The topics cover a large domain of research but place a particular emphasis on multiscale approaches at several length scales applied to non linear and heterogeneous materials. Discussions of new approaches are emphasised from various related disciplines, including metal physics, micromechanics, mathematical and computational mechanics.
Advanced Mathematical Science for Mobility Society
by Kazushi Ikeda Yoshiumi Kawamura Kazuhisa Makino Satoshi Tsujimoto Nobuo Yamashita Shintaro Yoshizawa Hanna SumitaThis open access book presents the mathematical methods for huge data and network analysis.The automotive industry has made steady progress in technological innovations under the names of Connected Autonomous-Shared-Electric (CASE) and Mobility as a Service (MaaS). Needless to say, mathematics and informatics are important to support such innovations. As the concept of cars and movement itself is diversifying, they are indispensable for grasping the essence of the future mobility society and building the foundation for the next generation. Based on this idea, Research unit named "Advanced Mathematical Science for Mobility Society" was established at Kyoto University as a base for envisioning a future mobility society in collaboration with researchers led by Toyota Motor Corporation and Kyoto University.This book contains three main contents.1. Mathematical models of flow2. Mathematical methodsfor huge data and network analysis3. Algorithm for mobility societyThe first one discusses mathematical models of pedestrian and traffic flow, as they are important for preventing accidents and achieving efficient transportation. The authors mainly focus on global dynamics caused by the interaction of particles. The authors discuss many-body particle systems in terms of geometry and box-ball systems. The second one consists of four chapters and deals with mathematical technologies for handling huge data related to mobility from the viewpoints of machine learning, numerical analysis, and statistical physics, which also includes blockchain techniques. Finally, the authors discuss algorithmic issues on mobility society. By making use of car-sharing service as an example of mobility systems, the authors consider how to construct and analyze algorithms for mobility system from viewpoints of control, optimization, and AI.
Advanced Mathematical Techniques in Computational and Intelligent Systems (Computational and Intelligent Systems)
by Sandeep Singh Aliakbar Montazer Haghighi Sandeep DalalThis book comprehensively discusses the modeling of real-world industrial problems and innovative optimization techniques such as heuristics, finite methods, operation research techniques, intelligent algorithms, and agent- based methods. Discusses advanced techniques such as key cell, Mobius inversion, and zero suffix techniques to find initial feasible solutions to optimization problems. Provides a useful guide toward the development of a sustainable model for disaster management. Presents optimized hybrid block method techniques to solve mathematical problems existing in the industries. Covers mathematical techniques such as Laplace transformation, stochastic process, and differential techniques related to reliability theory. Highlights application on smart agriculture, smart healthcare, techniques for disaster management, and smart manufacturing. Advanced Mathematical Techniques in Computational and Intelligent Systems is primarily written for graduate and senior undergraduate students, as well as academic researchers in electrical engineering, electronics and communications engineering, computer engineering, and mathematics.
Advanced Maya Texturing and Lighting
by Lee LanierIf you already understand the basics of Maya, the industry-leading 3D animation and effects software, you'll be ready to move on to the sophisticated topics in this updated edition of Advanced Maya Texturing and Lighting. Detailed, easy-to-follow instructions will teach you the real-world production secrets that professional animators use to achieve amazing results. In the second edition, you will find extensive and updated coverage of the latest theories and trends in addition to an enclosed CD with exclusive content to help you sharpen your skills.
Advanced Mechanics in Robotic Systems
by Nestor Eduardo Nava RodríguezHumans have always been fascinated with the concept of artificial life and the construction of machines that look and behave like people. As the field of robotics evolves, it demands continuous development of successful systems with high-performance characteristics for practical applications. Advanced Mechanics in Robotic Systems illustrates original and ambitious mechanical designs and techniques for developing new robot prototypes with successful mechanical operational skills. Case studies are focused on projects in mechatronics that have high growth expectations: humanoid robots,robotics hands,mobile robots,parallel manipulators, andhuman-centred robots.A good control strategy requires good mechanical design, so a chapter has also been devoted to the description of suitable methods for control architecture design. Readers of Advanced Mechanics in Robotic Systems will discover novel designs for relevant applications in robotic fields, that will be of particular interest to academic and industry-based researchers.
Advanced Metaprogramming in Classic C++
by Davide Di GennaroTake a detailed and intense look into template metaprogramming (TMP) using classic C++. Tackle language aspects, design patterns, examples and applications, with special emphasis on small reusable techniques that will improve the quality of daily work. Advanced Metaprogramming in Classic C++: Third Edition is a book to sit with and learn from. Users of its prior editions point out that they come back to it over and over. This edition enhances the readability and clarity of the discussion. The two newer standards are not used in the code so that the examples can be rich, illustrate the point, and be run with confidence. The code can be readily adapted to include the elements of the Modern C++ standards. The gain for the reader is that TMP is presented in the book as a set of techniques that will enable a new style to your C++ coding while making it exceptionally clear and efficient. The approach in the book is used to maximize compatibility and clearly illustrate the techniques, enabling the reader to comprehend difficult material without the burdens of compiler errors, and other unnecessary complexities and enabling a much more intense treatment of the subject. For those interested in Modern C++, all subsequent additions to the C++ language are fully compatible with the code in this book and users familiar with them can leverage the techniques introduced in C++XX to make the patterns in this book even more powerful. There is a chapter that discusses issues regarding the two newer standards and the basics needed to program for the newer standards are readily available online. What makes the book exceptional is the level of understanding of the concepts involved imparted by the author. This is not just a rote overview of metaprogramming. You will truly understand difficult topics like static assertions, how to write metafunctions, overload resolution, lambda expressions, and many others. More than that, you will work through them with practical examples guided by the author's frank explanations. This book requires you to think and to learn and to understand the language so that you can program at a higher level. What you'll learn What templates and the small object toolkit are, and how to use them How to do overload resolution How to do metaprogramming with interfaces, algorithms, functors and refactoring How to work with code generators What is opaque type principle and how to use it How to work with debugging templates and more A chapter devoted to issues surrounding C++0x and C++14 Who this book is for This book is for experienced C++ programmers who want to learn more. Table of Contents Part I 1. Templates 2. Small Object Toolkit Part II 3. Static Programming 4. Overload Resolution 5. Interfaces 6. Algorithms 7. Code Generators 8. Functors 9. Opaque Type Principle Part III 10. Refactoring 11. Debugging Templates 12. C++0X 13. Appendix A: Exercises 14. Appendix B: Bibliography
Advanced Methodologies for Bayesian Networks: Second International Workshop, AMBN 2015, Yokohama, Japan, November 16-18, 2015. Proceedings (Lecture Notes in Computer Science #9505)
by Joe Suzuki Maomi UenoThis volume constitutes the refereed proceedings of the Second International Workshop on Advanced Methodologies for Bayesian Networks, AMBN 2015, held in Yokohama, Japan, in November 2015. The 18 revised full papers and 6 invited abstracts presented were carefully reviewed and selected from numerous submissions. In the International Workshop on Advanced Methodologies for Bayesian Networks (AMBN), the researchers explore methodologies for enhancing the effectiveness of graphical models including modeling, reasoning, model selection, logic-probability relations, and causality. The exploration of methodologies is complemented discussions of practical considerations for applying graphical models in real world settings, covering concerns like scalability, incremental learning, parallelization, and so on.
Advanced Methods for Geometric Modeling and Numerical Simulation (Springer INdAM Series #35)
by Carlotta Giannelli Hendrik SpeleersThis book gathers selected contributions presented at the INdAM Workshop “DREAMS”, held in Rome, Italy on January 22−26, 2018. Addressing cutting-edge research topics and advances in computer aided geometric design and isogeometric analysis, it covers distinguishing curve/surface constructions and spline models, with a special focus on emerging adaptive spline constructions, fundamental spline theory and related algorithms, as well as various aspects of isogeometric methods, e.g. efficient quadrature rules and spectral analysis for isogeometric B-spline discretizations. Applications in finite element and boundary element methods are also discussed. Given its scope, the book will be of interest to both researchers and graduate students working in these areas.
Advanced Methods for Human Biometrics (Smart Sensors, Measurement and Instrumentation #40)
by Nabil Derbel Olfa KanounThe book highlights recent developments in human biometrics, covering a wide range of methods based on biological signals, image processing, and measurements of human characteristics such as fingerprints and iris or medical characteristics. Human Biometrics is becoming increasingly crucial in forensics security and medicine. They provide a solid basis for identifying individuals based on unique physical characteristics or diseases based on characteristic biomedical measurements. As such, the book offers an essential reference guide about biometry methods for students, engineers, designers, and technicians.
Advanced Methods in Automatic Item Generation
by Mark J. Gierl Hollis Lai Vasily TanyginAdvanced Methods in Automatic Item Generation is an up-to-date survey of the growing research on automatic item generation (AIG) in today’s technology-enhanced educational measurement sector. As test administration procedures increasingly integrate digital media and Internet use, assessment stakeholders—from graduate students to scholars to industry professionals—have numerous opportunities to study and create different types of tests and test items. This comprehensive analysis offers thorough coverage of the theoretical foundations and concepts that define AIG, as well as the practical considerations required to produce and apply large numbers of useful test items.
Advanced Methods in Computer Graphics: With examples in OpenGL
by Ramakrishnan MukundanThis book brings together several advanced topics in computer graphics that are important in the areas of game development, three-dimensional animation and real-time rendering. The book is designed for final-year undergraduate or first-year graduate students, who are already familiar with the basic concepts in computer graphics and programming. It aims to provide a good foundation of advanced methods such as skeletal animation, quaternions, mesh processing and collision detection. These and other methods covered in the book are fundamental to the development of algorithms used in commercial applications as well as research.
Advanced Methods of Solid Oxide Fuel Cell Modeling (Green Energy and Technology)
by Jarosław Milewski Pierluigi Leone Massimo Santarelli Konrad ŚwirskiFuel cells are widely regarded as the future of the power and transportation industries. Intensive research in this area now requires new methods of fuel cell operation modeling and cell design. Typical mathematical models are based on the physical process description of fuel cells and require a detailed knowledge of the microscopic properties that govern both chemical and electrochemical reactions. Advanced Methods of Solid Oxide Fuel Cell Modeling proposes the alternative methodology of generalized artificial neural networks (ANN) solid oxide fuel cell (SOFC) modeling. Advanced Methods of Solid Oxide Fuel Cell Modeling provides a comprehensive description of modern fuel cell theory and a guide to the mathematical modeling of SOFCs, with particular emphasis on the use of ANNs. Up to now, most of the equations involved in SOFC models have required the addition of numerous factors that are difficult to determine. The artificial neural network (ANN) can be applied to simulate an object's behavior without an algorithmic solution, merely by utilizing available experimental data. The ANN methodology discussed in Advanced Methods of Solid Oxide Fuel Cell Modeling can be used by both researchers and professionals to optimize SOFC design. Readers will have access to detailed material on universal fuel cell modeling and design process optimization, and will also be able to discover comprehensive information on fuel cells and artificial intelligence theory.