Mo Jamshidi – författare

In recent years, new paradigms have emerged to replace-or augment-the traditional, mathematically based approaches to optimization. The most powerful of these are genetic algorithms (GA), inspired by natural selection, and genetic programming, an extension of GAs based on the optimization of symbolic codes.Robust Control Systems with Genetic Algorithms builds a bridge between genetic algorithms and the design of robust control systems. After laying a foundation in the basics of GAs and genetic programming, it demonstrates the power of these new tools for developing optimal robust controllers for linear control systems, optimal disturbance rejection controllers, and predictive and variable structure control. It also explores the application of hybrid approaches: how to enhance genetic algorithms and programming with fuzzy logic to design intelligent control systems. The authors consider a variety of applications, such as the optimal control of robotic manipulators, flexible links and jet engines, and illustrate a multi-objective, genetic algorithm approach to the design of robust controllers with a gasification plant case study.The authors are all masters in the field and clearly show the effectiveness of GA techniques. Their presentation is your first opportunity to fully explore this cutting-edge approach to robust optimal control system design and exploit its methods for your own applications.

This book examines the nature of emergence in context of man-made (i.e. engineered) systems, in general, and system of systems engineering applications, specifically. It investigates emergence to interrogate or explore the domain space from a modeling and simulation perspective to facilitate understanding, detection, classification, prediction, control, and visualization of the phenomenon. Written by leading international experts, the text is the first to address emergence from an engineering perspective."System engineering has a long and proud tradition of establishing the integrative view of systems. The field, however, has not always embraced and assimilated well the lessons and implications from research on complex adaptive systems. As the editors’ note, there have been no texts on Engineering Emergence: Principles and Applications. It is therefore especially useful to have this new, edited book that pulls together so many of the key elements, ranging from the theoretical to the practical, and tapping into advances in methods, tools, and ways to study system complexity. Drs. Rainey and Jamshidi are to be congratulated both for their vision of the book and their success in recruiting contributors with so much to say. Most notable, however, is that this is a book with engineering at its core. It uses modeling and simulation as the language in which to express principles and insights in ways that include tight thinking and rigor despite dealing with notably untidy and often surprising phenomena."— Paul K. Davis, RAND and Frederick S. Pardee RAND Graduate School The first chapter is an introduction and overview to the text. The book provides 12 chapters that have a theoretical foundation for this subject. Includes 7 specific example chapters of how various modeling and simulation paradigms/techniques can be used to investigate emergence in an engineering context to facilitate understanding, detection, classification, prediction, control and visualization of emergent behavior. The final chapter offers lessons learned and the proposed way-ahead for this discipline.

Smart Cities: A System-of-Systems Perspective explores System-of-Systems Engineering (SoSE) in smart cities. Sections address how analytics and innovative technologies can transform urban environments, equipping readers with the knowledge to optimize city operations, enhance public services, and promote sustainable urban growth. The book begins with the foundational concepts of SoSE and key principles of smart cities, exploring emergent behavior and interoperability. It then examines the integration of SoSE within urban infrastructure, highlighting the roles of IoT, AI, and machine learning. Subsequent sections focus on core technologies and analytical tools, including data analytics, predictive modeling, and decision support systems.Readers will also discover innovative solutions to pressing urban challenges, such as sustainability, cybersecurity, and governance, alongside detailed case studies showcasing successful smart city initiatives from around the globe. This book is invaluable for academics and researchers in urban studies, engineering, analytics, IoT, and AI, as well as data scientists and analytics professionals working with urban datasets. Graduate and postgraduate students in engineering, analytics, computer science, or urban studies will also find it a crucial resource.Covers both theoretical foundations and practical methodologiesUses real-world examples to make the concepts accessible and actionableProvides innovative strategies and tools to address the challenges faced by urban planners and system engineers, such as interoperability between systems, scalability, sustainability, and emergent behavior managementIncludes detailed, practical case studies of successful smart city projects worldwide, showcasing best practices, challenges, and lessons learned and offering valuable insights for replicating and adapting smart city solutionsExplores cutting-edge technologies such as AI, IoT, 5G, and renewable energy integration, providing readers with an understanding of how these innovations are transforming urban systems and highlighting future trends and opportunities in smart city developmentOffers decision-making and policy support frameworks, optimization techniques, and governance models to help readers navigate the complexities of multi-stakeholder collaboration

In recent years, new paradigms have emerged to replace-or augment-the traditional, mathematically based approaches to optimization. The most powerful of these are genetic algorithms (GA), inspired by natural selection, and genetic programming, an extension of GAs based on the optimization of symbolic codes.Robust Control Systems with Genetic Algorithms builds a bridge between genetic algorithms and the design of robust control systems. After laying a foundation in the basics of GAs and genetic programming, it demonstrates the power of these new tools for developing optimal robust controllers for linear control systems, optimal disturbance rejection controllers, and predictive and variable structure control. It also explores the application of hybrid approaches: how to enhance genetic algorithms and programming with fuzzy logic to design intelligent control systems. The authors consider a variety of applications, such as the optimal control of robotic manipulators, flexible links and jet engines, and illustrate a multi-objective, genetic algorithm approach to the design of robust controllers with a gasification plant case study.The authors are all masters in the field and clearly show the effectiveness of GA techniques. Their presentation is your first opportunity to fully explore this cutting-edge approach to robust optimal control system design and exploit its methods for your own applications.

In recent years, intelligent control has emerged as one of the most active and fruitful areas of research and development. Until now, however, there has been no comprehensive text that explores the subject with focus on the design and analysis of biological and industrial applications. Intelligent Control Systems Using Soft Computing Methodologies does all that and more. Beginning with an overview of intelligent control methodologies, the contributors present the fundamentals of neural networks, supervised and unsupervised learning, and recurrent networks. They address various implementation issues, then explore design and verification of neural networks for a variety of applications, including medicine, biology, digital signal processing, object recognition, computer networking, desalination technology, and oil refinery and chemical processes.The focus then shifts to fuzzy logic, with a review of the fundamental and theoretical aspects, discussion of implementation issues, and examples of applications, including control of autonomous underwater vehicles, navigation of space vehicles, image processing, robotics, and energy management systems. The book concludes with the integration of genetic algorithms into the paradigm of soft computing methodologies, including several more industrial examples, implementation issues, and open problems and open problems related to intelligent control technology.Suitable as a textbook or a reference, Intelligent Control Systems explores recent advances in the field from both the theoretical and the practical viewpoints. It also integrates intelligent control design methodologies to give designers a set of flexible, robust controllers and provide students with a tool for solving the examples and exercises within the book.

This book examines the nature of emergence in context of man-made (i.e. engineered) systems, in general, and system of systems engineering applications, specifically. It investigates emergence to interrogate or explore the domain space from a modeling and simulation perspective to facilitate understanding, detection, classification, prediction, control, and visualization of the phenomenon. Written by leading international experts, the text is the first to address emergence from an engineering perspective."System engineering has a long and proud tradition of establishing the integrative view of systems. The field, however, has not always embraced and assimilated well the lessons and implications from research on complex adaptive systems. As the editors’ note, there have been no texts on Engineering Emergence: Principles and Applications. It is therefore especially useful to have this new, edited book that pulls together so many of the key elements, ranging from the theoretical to the practical, and tapping into advances in methods, tools, and ways to study system complexity. Drs. Rainey and Jamshidi are to be congratulated both for their vision of the book and their success in recruiting contributors with so much to say. Most notable, however, is that this is a book with engineering at its core. It uses modeling and simulation as the language in which to express principles and insights in ways that include tight thinking and rigor despite dealing with notably untidy and often surprising phenomena."— Paul K. Davis, RAND and Frederick S. Pardee RAND Graduate School The first chapter is an introduction and overview to the text. The book provides 12 chapters that have a theoretical foundation for this subject. Includes 7 specific example chapters of how various modeling and simulation paradigms/techniques can be used to investigate emergence in an engineering context to facilitate understanding, detection, classification, prediction, control and visualization of emergent behavior. The final chapter offers lessons learned and the proposed way-ahead for this discipline.

As technology presses forward, scientific projects are becoming increasingly complex. The international space station, for example, includes over 100 major components, carried aloft during 88 spaces flights which were organized by over 16 nations. The need for improved system integration between the elements of an overall larger technological system has sparked further development of systems of systems (SoS) as a solution for achieving interoperability and superior coordination between heterogeneous systems. Systems of Systems Engineering: Principles and Applications provides engineers with a definitive reference on this newly emerging technology, which is being embraced by such engineering giants as Boeing, Lockheed Martin, and Raytheon. The book covers the complete range of fundamental SoS topics, including modeling, simulation, architecture, control, communication, optimization, and applications. Containing the contributions of pioneers at the forefront of SoS development, the book also offers insight into applications in national security, transportation, energy, and defense as well as healthcare, the service industry, and information technology. System of systems (SoS) is still a relatively new concept, and in time numerous problems and open-ended issues must be addressed to realize its great potential. THis book offers a first look at this rapidly developing technology so that engineers are better equipped to face such challenges.

From aeronautics and manufacturing to healthcare and disaster management, systems engineering (SE) now focuses on designing applications that ensure performance optimization, robustness, and reliability while combining an emerging group of heterogeneous systems to realize a common goal. Use SoS to Revolutionize Management of Large Organizations, Factories, and Systems Intelligent Control Systems with an Introduction to System of Systems Engineering integrates the fundamentals of artificial intelligence and systems control in a framework applicable to both simple dynamic systems and large-scale system of systems (SoS). For decades, NASA has used SoS methods, and major manufacturers—including Boeing, Lockheed-Martin, Northrop-Grumman, Raytheon, BAE Systems—now make large-scale systems integration and SoS a key part of their business strategies, dedicating entire business units to this remarkably efficient approach.Simulate Novel Robotic Systems and ApplicationsTranscending theory, this book offers a complete and practical review of SoS and some of its fascinating applications, including: Manipulation of robots through neural-based network control Use of robotic swarms, based on ant colonies, to detect mines Other novel systems in which intelligent robots, trained animals, and humans cooperate to achieve humanitarian objectivesTraining engineers to integrate traditional systems control theory with soft computing techniques further nourishes emerging SoS technology. With this in mind, the authors address the fundamental precepts at the core of SoS, which uses human heuristics to model complex systems, providing a scientific rationale for integrating independent, complex systems into a single coordinated, stabilized, and optimized one. They provide readers with MATLAB® code, which can be downloaded from the publisher's website to simulate presented results and projects that offer practical, hands-on experience using concepts discussed throughout the book.

This book presents the proceedings of the 13th International Conference on Application of Fuzzy Systems and Soft Computing (ICAFS 2018), held in Warsaw, Poland on August 27–28, 2018. It includes contributions from diverse areas of soft computing such as uncertain computation, Z-information processing, neuro-fuzzy approaches, evolutionary computing and others. The topics of the papers include theory of uncertainty computation; theory and application of soft computing; decision theory with imperfect information; neuro-fuzzy technology; image processing with soft computing; intelligent control; machine learning; fuzzy logic in data analytics and data mining; evolutionary computing; chaotic systems; soft computing in business, economics and finance; fuzzy logic and soft computing in the earth sciences; fuzzy logic and soft computing in engineering; soft computing in medicine, biomedical engineering and the pharmaceutical sciences; and probabilistic and statistical reasoning in the social and educational sciences. The book covers new ideas from theoretical and practical perspectives in economics, business, industry, education, medicine, the earth sciences and other fields. In addition to promoting the development and application of soft computing methods in various real-life fields, it offers a useful guide for academics, practitioners, and graduates in fuzzy logic and soft computing fields.

This book presents the proceedings of the 10th Conference on Theory and Applications of Soft Computing, Computing with Words and Perceptions, ICSCCW 2019, held in Prague, Czech Republic, on August 27–28, 2019. It includes contributions from diverse areas of soft computing and computing with words, such as uncertain computation, decision-making under imperfect information, neuro-fuzzy approaches, deep learning, natural language processing, and others. The topics of the papers include theory and applications of soft computing, information granulation, computing with words, computing with perceptions, image processing with soft computing, probabilistic reasoning, intelligent control, machine learning, fuzzy logic in data analytics and data mining, evolutionary computing, chaotic systems, soft computing in business, economics and finance, fuzzy logic and soft computing in earth sciences, fuzzy logic and soft computing in engineering, fuzzy logic and soft computing in material sciences,soft computing in medicine, biomedical engineering, and pharmaceutical sciences. Showcasing new ideas in the field of theories of soft computing and computing with words and their applications in economics, business, industry, education, medicine, earth sciences, and other fields, it promotes the development and implementation of these paradigms in various real-world contexts. This book is a useful guide for academics, practitioners and graduates.

This book presents the proceedings of the 14th International Conference on Applications of Fuzzy Systems, Soft Computing, and Artificial Intelligence Tools, ICAFS-2020, held in Budva, Montenegro, on August 27–28, 2020.

This book presents the proceedings of the 11th Conference on Theory and Applications of Soft Computing, Computing with Words and Perceptions and Artificial Intelligence, ICSCCW-2021, held in Antalya, Turkey, on August 23–24, 2021. The general scope of the book covers uncertain computation, decision making under imperfect information, neuro-fuzzy approaches, natural language processing, and other areas. The topics of the papers include theory and application of soft computing, computing with words, image processing with soft computing, intelligent control, machine learning, fuzzy logic in data mining, soft computing in business, economics, engineering, material sciences, biomedical engineering, and health care.This book is a useful guide for academics, practitioners, and graduates in fields of soft computing and computing with words. It allows for increasing of interest in development and applying of these paradigms in various real-life fields.

The general scope of the book covers diverse areas of fuzzy systems, soft computing, AI tools such as uncertain computation, decision-making under imperfect information, deep learning, and others. The topics of the papers include theory and application of Soft Computing, Neuro-Fuzzy Technology, Intelligent Control, Deep Learning-Machine Learning, Fuzzy Logic in Data Analytics, Evolutionary Computing, Fuzzy logic and Artificial Intelligence in Engineering, Social Sciences, Business, Economics, Material Sciences, and others.This book presents the proceedings of the 16th International Conference on Applications of Fuzzy Systems, Soft Computing, and Artificial Intelligence Tools, ICAFS-2022, held in Budva, Montenegro, on August 26-27, 2022. This is a useful guide for academics, practitioners, and graduates in fields of fuzzy logic and soft computing. It allows for increasing of interest in development and applying of these paradigms in various real-life fields.

This book covers diverse areas of fuzzy logic, soft computing, and AI approaches such as uncertain computation, decision-making under imperfect information, deep learning, and others. The topics of the papers include theory and application of soft computing, decision theory with imperfect information, neuro-fuzzy technology, intelligent control, machine learning, evolutionary computing, fuzzy logic, and soft computing in engineering, industry, social sciences, business, economics, earth sciences, material sciences, and others.This book presents the proceedings of the 16th International Conference on Applications of Fuzzy Systems, Soft Computing, and Artificial Intelligence Tools, ICAFS-2023, held in Antalya, Turkey, on September 14–15, 2023. This will be a useful guide for academics, practitioners, and graduates in fields of fuzzy systems and soft computing. It would allow for attracting of interest in development and applying of these paradigms in various real fields.

This book covers diverse areas of fuzzy logic, soft computing, and AI approaches such as uncertain computation, decision-making under imperfect information, deep learning, and others. The topics of the papers include theory and application of soft computing, decision theory with imperfect information, neuro-fuzzy technology, intelligent control, machine learning, evolutionary computing, fuzzy logic, and soft computing in engineering, industry, social sciences, business, economics, earth sciences, material sciences, and others.This book presents the proceedings of the 16th International Conference on Applications of Fuzzy Systems, Soft Computing, and Artificial Intelligence Tools, ICAFS-2023, held in Antalya, Turkey, on September 14–15, 2023. This will be a useful guide for academics, practitioners, and graduates in fields of fuzzy systems and soft computing. It would allow for attracting of interest in development and applying of these paradigms in various real fields.

This book is the proceedings of the 3rd World Conference on Soft Computing (WCSC), which was held in San Antonio, TX, USA, on December 16-18, 2013. It presents start-of-the-art theory and applications of soft computing together with an in-depth discussion of current and future challenges in the field, providing readers with a 360 degree view on soft computing. Topics range from fuzzy sets, to fuzzy logic, fuzzy mathematics, neuro-fuzzy systems, fuzzy control, decision making in fuzzy environments, image processing and many more. The book is dedicated to Lotfi A. Zadeh, a renowned specialist in signal analysis and control systems research who proposed the idea of fuzzy sets, in which an element may have a partial membership, in the early 1960s, followed by the idea of fuzzy logic, in which a statement can be true only to a certain degree, with degrees described by numbers in the interval [0,1]. The performance of fuzzy systems can often be improved with the help of optimization techniques, e.g. evolutionary computation, and by endowing the corresponding system with the ability to learn, e.g. by combining fuzzy systems with neural networks. The resulting “consortium” of fuzzy, evolutionary, and neural techniques is known as soft computing and is the main focus of this book.