This basic book has been used at the middle schools in Shanghai, China for more than 10 years. The book presents carefully-selected contents in order to achieve the roles of enlightenment and popularization. It mainly includes: Chapter 1: Human Brains, Computers and Fuzzy Mathematics; Chapter 2: Matrix, Fuzzy Relations and Fuzzy Matrix; Chapter 3: Fuzzy Control; Chapter 4: Fuzzy Statistics and Fuzzy Probability and Chapter 5: Fuzzy Linear Programming. It includes at the end of each chapter concise, interesting and profound reading and thinking materials, and a certain amount of exercises so as to make it an informative and interesting textbook. This book can be used not only as a textbook in senior middle schools, and in vocational colleges, but also as a primer for individually learning fuzzy mathematics.

Provides a comprehensive review on new swarm intelligence Offers practical implementation of PSO with MATLAB code Presents statistical analysis techniques so that researchers can analyze their own experiment design Discusses swarm intelligence algorithms in social sector and oil and gas industries Covers recent findings and the implementation techniques to Machine Learning

- Ties together the three (now) competing modern disciplines in Program and Project Management - Tells you how to do it, not just some theory based on a one of a kind project - Provides clear and concise definitions for the three disciplines helping with career choices, separation of duties and when to use - Perfect desktop reference usable for many years to come

This book, published in honor of Professor Laurent Praly on the occasion of his 65th birthday, explores the responses of some leading international authorities to new challenges in nonlinear and adaptive control. The mitigation of the effects of uncertainty and nonlinearity - ubiquitous features of real-world engineering and natural systems - on closed-loop stability and robustness being of crucial importance, the contributions report the latest research into overcoming these difficulties in: autonomous systems; reset control systems; multiple-input-multiple-output nonlinear systems; input delays; partial differential equations; population games; and data-driven control. Trends in Nonlinear and Adaptive Control presents research inspired by and related to Professor Praly's lifetime of contributions to control theory and is a valuable addition to the literature of advanced control.

Co-location pattern mining detects sets of features frequently located in close proximity to each other. This book focuses on data mining for co-location pattern, a valid method for identifying patterns from all types of data and applying them in business intelligence and analytics. It explains the fundamentals of co-location pattern mining, co-location decision tree, and maximal instance co-location pattern mining along with an in-depth overview of data mining, machine learning, and statistics. This arrangement of chapters helps readers understand the methods of co-location pattern mining step-by-step and their applications in pavement management, image classification, geospatial buffer analysis, etc.

The insertion of communication networks in feedback control loops complicates analysis and synthesis of cyber-physical systems (CPSs), and network-induced uncertainties may degrade system control performance. Thus, this book researches networked delay compensation and event-triggered control approaches for a series of CPSs subject to network-induced uncertainties. The authors begin with an introduction to the concepts and challenges of CPSs, followed by an overview of networked control approaches and event-triggered control strategies in CPSs. Then, networked delay compensation and event-triggered control approaches are proposed for CPSs with network communication delay, data dropout, signal quantization, and event-triggered communication. More specifically, networked delay compensation approaches are proposed for linear/nonlinear networked controlled plants with time-varying and random network communication delays and data dropouts. To reduce computational burden and network communication loads in CPSs, event-triggered control, self-triggered control, co-design of event-triggered control and quantized control techniques, and event-triggered disturbance rejection control approaches are also presented. This book is an essential text for researchers and engineers interested in cybersecurity, networked control, and CPSs. It would also prove useful for graduate students in the fields of science, engineering, and computer science.

This book, along with its companion volume, Nonlinear Dynamics New Directions: Theoretical Aspects, covers topics ranging from fractal analysis to very specific applications of the theory of dynamical systems to biology. This second volume contains mostly new applications of the theory of dynamical systems to both engineering and biology. The first volume is devoted to fundamental aspects and includes a number of important new contributions as well as some review articles that emphasize new development prospects. The topics addressed in the two volumes include a rigorous treatment of fluctuations in dynamical systems, topics in fractal analysis, studies of the transient dynamics in biological networks, synchronization in lasers, and control of chaotic systems, among others. This book also: * Develops applications of nonlinear dynamics on a diversity of topics such as patterns of synchrony in neuronal networks, laser synchronization, control of chaotic systems, and the study of transient dynamics in biological * Includes a study of self-organized regularity in long-range systems * Explains use of Levenstein's distance for measuring lexical evolution rates

The effectiveness of proportional-integral-derivative (PID) controllers for a large class of process systems has ensured their continued and widespread use in industry. Similarly there has been a continued interest from academia in devising new ways of approaching the PID tuning problem.

To the industrial engineer and many control academics this work has previously appeared fragmented but a key determinant of this literature is the type of process model information used in the PID tuning methods. PID Control presents a set of coordinated contributions illustrating methods, old and new, that cover the range of process model assumptions systematically. After a review of PID technology, these contributions begin with model-free methods, progress through non-parametric model methods (relay experiment and phase-locked-loop procedures), visit fuzzy-logic- and genetic-algorithm-based methods; introduce a novel subspace identification method before closing with an interesting set of parametric model techniques including a chapter on predictive PID controllers.

Highlights of PID Control include:

• an introduction to PID control technology features and typical industrial implementations;
• chapter contributions ordered by the increasing quality of the model information used;
• novel PID control concepts for multivariable processes.

PID Control will be useful to industry-based engineers wanting a better understanding of what is involved in the steps to a new generation of PID controller techniques. Academics wishing to have a broader perspective of PID control research and development will find useful pedagogical material and research ideas in this text.

Viability theory designs and develops mathematical and algorithmic methods for investigating the adaptation to viability constraints of evolutions governed by complex systems under uncertainty that are found in many domains involving living beings, from biological evolution to economics, from environmental sciences to financial markets, from control theory and robotics to cognitive sciences. It involves interdisciplinary investigations spanning fields that have traditionally developed in isolation. The purpose of this book is to present an initiation to applications of viability theory, explaining and motivating the main concepts and illustrating them with numerous numerical examples taken from various fields.

This book shows some secure control methods of networked control systems related to linear control system, nonlinear control system, multi-agent system and its applications in power systems. The proposed secure control methods provide some useful results about modeling of network attacks, resilient analysis and synthesis methods, active defense control method.The contents of this book are lists as followings. (1) Modeling of DoS attacks, deception attacks and replay attacks; (2)Secure control methods are proposed by combing delay system method, switched system method and event-based control method. (3) Active control methods are proposed by using model-predictive control and redundant control. (4) The proposed control methods are applied to the security problem of power system.The methods of this book include DoS attacks modeling such as, periodic jamming attack model,model-based average dwell time model, deception attack modeling and relay attack modeling; piece-wise Lyapunov-Krasoviskiifunctional method, stochastic control method; the results including resilient conditions of networked control system and related resilient control design method with linear matrix inequalities(LMIs).From this book, readers can learn about the general network attack modeling methods, resilient analysis and synthesis methods, active control methods from viewpoint of redundancy control, and secure conditions of power systems.Some fundamental knowledge prepared to read this book includes delay system theory, event triggered mechanism, T-S fuzzy system theory and frequency/voltage control of power system.

This is a comprehensive book on how to make complex decisions on energy systems problems involving different technologies, environmental effects, costs, benefits, risks, and safety issues. Using Industrial and Systems Engineering techniques for decision-making in Energy Systems, the book provides the background knowledge and methods to incorporate multiple criteria involved in solving energy system problems. It offers methods, examples, and case studies illustrating applications. Decision-Making in Energy Systems discusses subjective as well as objective methods, approaches, and techniques taken from the systems and industrial engineering domain and puts them to use in solving energy systems problems. It uses an integrated approach by including effects of all technical, economic, environmental, and safety considerations as well as costs and risks. The book is specially designed for practicing engineers from industrial/systems engineering who work in energy systems engineering industries. Aimed at graduate students, researchers, and managers involved in various energy generating, distributing, and consuming companies, the book helps the reader to understand, evaluate, and decide on solutions to their energy-related problems.

Discusses wide range of magnetic field assisted finishing processes in a comprehensive manner. Covers different process parameters by considering their effects on the finishing output. Provides process limitations to achieve optimal yield. Covers numerical explanations for better selection of process parameters. Discusses automation of processes with state-of-the-art technologies.

Provides the details of state-of-the-art machine learning methods used in VLSI Design. Discusses hardware implementation and device modeling pertaining to machine learning algorithms. Explores machine learning for various VLSI architectures and reconfigurable computing. Illustrate latest techniques for device size and feature optimization. Highlight latest case studies and reviews of the methods used for hardware implementation.

1 uniquely integrates essentials from vehicle dynamics and control theory for controller design with NI LabVIEW at the level of practical applications 2 Provides new features in the modelling of drivetrain configuration, regenerative braking, rollover dynamics for model-based control 3 Shares advanced controller designs that have yet to be published 4 Provides mathematical models of vehicle behavior of vehicles that move dynamically in the presence of disturbances to the motion 5 Demonstrates what a control design engineer can do to practically achieve the desired vehicle behavior based on mathematical models

Examines the recent research trends and the future of Cyber-Physical systems, IoT, and Autonomous Systems as it relates to Industry 4.0 Investigates various challenges across multiple sectors and different industries Offers a discussion on the recent advancements in Industry 4.0 technological developments for operations and supply chain management Explores the potential for the IoT, Autonomous and Cyber-Physical Systems to replace the current mechanical, people-based systems in various sectors Discusses additional topics such as Machine Learning and Cloud Computing

Examines how digital media and the creation of digital immortals may affect religious understandings of death and the afterlife; Understands the impact of digital media on those living and those working with the bereaved; Explores the impact of digital memorialisation post death; Looks at the ways in which digital media may be changing conceptions and theologies of death

Examines how digital media and the creation of digital immortals may affect religious understandings of death and the afterlife; Understands the impact of digital media on those living and those working with the bereaved; Explores the impact of digital memorialisation post death; Looks at the ways in which digital media may be changing conceptions and theologies of death

The book intends to cover various problematic aspects of emerging smart computing and self-adapting technologies comprising of machine learning, artificial intelligence, deep learning, robotics, cloud computing, fog computing, data mining algorithms, including emerging intelligent and smart applications related to these research areas. Further coverage includes implementation of self-adaptation architecture for smart devices, self-adaptive models for smart cities and self-driven cars, decentralized self-adaptive computing at the edge networks, energy-aware AI-based systems, M2M networks, sensors, data analytics, algorithms and tools for engineering self-adaptive systems, and so forth. Acts as guide to Self-healing and Self-adaptation based fully automatic future technologies Discusses about Smart Computational abilities and self-adaptive systems Illustrates tools and techniques for data management and explains the need to apply, and data integration for improving efficiency of big data Exclusive chapter on the future of self-stabilizing and self-adaptive systems of systems Covers fields such as automation, robotics, medical sciences, biomedical and agricultural sciences, healthcare and so forth This book is aimed researchers and graduate students in machine learning, information technology, and artificial intelligence.

1) Focuses on the concepts and implementation strategies of various Deep Learning algorithms through properly curated examples. 2) The subject area will be valid for the next 10 years or so, as Deep Learning theory/algorithms and their applications will not be outdated easily. Hence there will be demand for such a book in the market. 3) In comparison to other titles, this book rigorously covers mathematical and conceptual details of relevant topics.

Considers both time-domain and frequency domain robust design techniques of partial differential systems Illustrates both theoretical robust design techniques and practical applications Discusses partial differential systems with both Dirichlet and Neuman boundary conditions in robust design procedure Addresses deterministic and stochastic partial differential systems Explores theoretical mathematical background, robust signal processing design, robust control system design and robust biological system design with application

Systems-Level Modelling of Microbial Communities: Theory and Practice introduces various aspects of modelling microbial communities and presents a detailed overview of the computational methods which have been developed in this area. This book is aimed at researchers in the field of computational/systems biology as well as biologists/experimentalists studying microbial communities, who are keen on embracing the concepts of computational modelling. The primary focus of this book is on methods for modelling interactions between micro-organisms in a community, with special emphasis on constraint-based and network-based modelling techniques. A brief overview of population- and agent-based modelling is also presented. Lastly, it covers the experimental methods to understand microbial communities, and provides an outlook on how the field may evolve in the coming years.

This book categorizes the wide area of data-driven model-free controllers, reveals the exact benefits of such controllers, gives the in-depth theory and mathematical proofs behind them, and finally discusses their applications. Each chapter includes a section for presenting the theory and mathematical definitions of one of the above mentioned algorithms. The second section of each chapter is dedicated to the examples and applications of the corresponding control algorithms in practical engineering problems. This book proposes to avoid complex mathematical equations, being generic as it includes several types of data-driven model-free controllers, such as Iterative Feedback Tuning controllers, Model-Free Controllers (intelligent PID controllers), Model-Free Adaptive Controllers, model-free sliding mode controllers, hybrid model-free and model-free adaptive-Virtual Reference Feedback Tuning controllers, hybrid model-free and model-free adaptive fuzzy controllers and cooperative model-free controllers. The book includes the topic of optimal model-free controllers, as well. The optimal tuning of model-free controllers is treated in the chapters that deal with Iterative Feedback Tuning and Virtual Reference Feedback Tuning. Moreover, the extension of some model-free control algorithms to the consensus and formation-tracking problem of multi-agent dynamic systems is provided. This book can be considered as a textbook for undergraduate and postgraduate students, as well as a professional reference for industrial and academic researchers, attracting the readers from both industry and academia.

This book focuses on engineering design approaches for spacecraft antennas. Based on their functions in spacecraft, it discusses practical antenna design, measurement and testing. Most of the antennas covered originated at the China Academy of Space Technology (CAST), which has launched almost 300 satellites into orbit. The book presents antenna systems for seven existing spacecraft designs, while also introducing readers to new antenna technologies for spacecraft. This book is intended for researchers, graduate students, and engineers in various fields of aerospace technology and astronautics, especially spacecraft design, communication engineering and related areas.

The fourth edition of this bestselling textbook explains the principles of artificial intelligence (AI) and its practical applications. Using clear and concise language, it provides a solid grounding across the full spectrum of AI techniques, so that its readers can implement systems in their own domain of interest. The coverage includes knowledge-based intelligence, computational intelligence (including machine learning), and practical systems that use a combination of techniques. All the key techniques of AI are explained-including rule-based systems, Bayesian updating, certainty theory, fuzzy logic (types 1 and 2), agents, objects, frames, symbolic learning, case-based reasoning, genetic algorithms and other optimization techniques, shallow and deep neural networks, hybrids, and the Lisp, Prolog, and Python programming languages. The book also describes a wide range of practical applications in interpretation and diagnosis, design and selection, planning, and control. Fully updated and revised, Intelligent Systems for Engineers and Scientists: A Practical Guide to Artificial Intelligence, Fourth Edition features: A new chapter on deep neural networks, reflecting the growth of machine learning as a key technique for AI A new section on the use of Python, which has become the de facto standard programming language for many aspects of AI The rule-based and uncertainty-based examples in the book are compatible with the Flex toolkit by Logic Programming Associates (LPA) and its Flint extension for handling uncertainty and fuzzy logic. Readers of the book can download this commercial software for use free of charge. This resource and many others are available at the author's website: adrianhopgood.com. Whether you are building your own intelligent systems, or you simply want to know more about them, this practical AI textbook provides you with detailed and up-to-date guidance.

The fourth edition of this bestselling textbook explains the principles of artificial intelligence (AI) and its practical applications. Using clear and concise language, it provides a solid grounding across the full spectrum of AI techniques, so that its readers can implement systems in their own domain of interest. The coverage includes knowledge-based intelligence, computational intelligence (including machine learning), and practical systems that use a combination of techniques. All the key techniques of AI are explained-including rule-based systems, Bayesian updating, certainty theory, fuzzy logic (types 1 and 2), agents, objects, frames, symbolic learning, case-based reasoning, genetic algorithms and other optimization techniques, shallow and deep neural networks, hybrids, and the Lisp, Prolog, and Python programming languages. The book also describes a wide range of practical applications in interpretation and diagnosis, design and selection, planning, and control. Fully updated and revised, Intelligent Systems for Engineers and Scientists: A Practical Guide to Artificial Intelligence, Fourth Edition features: A new chapter on deep neural networks, reflecting the growth of machine learning as a key technique for AI A new section on the use of Python, which has become the de facto standard programming language for many aspects of AI The rule-based and uncertainty-based examples in the book are compatible with the Flex toolkit by Logic Programming Associates (LPA) and its Flint extension for handling uncertainty and fuzzy logic. Readers of the book can download this commercial software for use free of charge. This resource and many others are available at the author's website: adrianhopgood.com. Whether you are building your own intelligent systems, or you simply want to know more about them, this practical AI textbook provides you with detailed and up-to-date guidance.