This book, the outcome of a workshop meeting within ESM 2006, explores the use of emergent computing and self-organization modeling within various applications of complex systems.

The breakthrough of AI in the design of complex systems in our daily lives has prompted researchers around the world to integrate this paradigm into their work. From simple citizens to large industrialists, including academics and politicians, there is a great enthusiasm for making all objects intelligent. This has led the scientific community to develop complex intelligent systems adaptable to different real-life systems. This book, which is a selective collection of research papers accepted by the international program committee of the 7th international symposium on Modeling and Implementation of Complex Systems (MISC 2022), makes its contribution in this vast field and addresses subjects that are as interesting as they are useful to the citizen life, namely In healthcare: health monitoring systems for heart patients, a model for cardiovascular disease prediction, early diabetic detection, COVID-19 screening from cough sound, and detection in epidemiological diseases. In natural language processing: summarization of major Arabic machine translation corpora, impact of normalization, and data augmentation on named entity recognition (NER) task on Algerian text. In Agriculture 5.0: schedule of the most widely used IoT architectures and plant recognition. In robotics: visually real-time control of a mobile EV3 robot in an indoor environment. In social media: the identification of rumors on social networks. In computer vision and biometrics: illumination-robust face recognition system. In IoT ecosystem, networks and cloud computing: technologies and protocols, architectures and modeling IoT applications, Named Data Networking (NDN) for the emergent IoT, unmanned aerial vehicle carried base stations (UAV-BSs) placement problem in 5G networks, assignment of the submitted tasks to the available resources in a cloud computing environment, providing routes in the presence of obstacles, and security aspects. Finally, the reader finds how to approach problems even if they have no algorithmic or no exact solution by using the following techniques developed in the different chapters of this book: deep CNN models and dense CNN models, voluntary simulation, hybrid gray wolf optimizer (GWO), multi-verse optimizer (MVO), coronavirus herd immunity optimizer (CHIO) algorithm, multi-population differential evolution, graphical formalism with machine learning and Color Petri Nets, and extension of BPMN 2.0.

This book discusses the latest progresses and developments on complex systems research and intends to give an exposure to prospective readers about the theoretical and practical aspects of mathematical modelling, numerical simulation and agent-based modelling frameworks. The main purpose of this book is to emphasize a unified approach to complex systems analysis, which goes beyond to examine complicated phenomena of numerous real-life systems; this is done by investigating a huge number of components that interact with each other at different (microscopic and macroscopic) scales; new insights and emergent collective behaviours can evolve from the interactions between individual components and also with their environments. These tools and concepts permit us to better understand the patterns of various real-life systems and help us to comprehend the mechanisms behind which distinct factors shaping some complex systems phenomena being influenced. This book is published in conjunction with the International Workshop on Complex Systems Modelling & Simulation 2019 (CoSMoS 2019): IoT & Big Data Integration. This international event was held at the Universiti Sains Malaysia Main Campus, Penang, Malaysia, from 8 to 11 April 2019. This book appeals to readers interested in complex systems research and other related areas such as mathematical modelling, numerical simulation and agent-based modelling frameworks.

Robert Siegfried presents a framework for efficient agent-based modeling and simulation of complex systems. He compares different approaches for describing structure and dynamics of agent-based models in detail. Based on this evaluation the author introduces the “General Reference Model for Agent-based Modeling and Simulation” (GRAMS). Furthermore he presents parallel and distributed simulation approaches for execution of agent-based models –from small scale to very large scale. The author shows how agent-based models may be executed by different simulation engines that utilize underlying hardware resources in an optimized fashion.

Complexity systems are at the heart of behavior

This book provides readers with an overview of recent theories and methods for studying complex mechanical systems used in energy production, such as wind turbines, but not limited to them. The emphasis is put on strategies for increasing energy efficiency, and on recent industrial applications. Topics cover dynamics and vibration, vibroacoustics, engineering design, modelling and simulation, fault diagnostics, signal processing and prognostics. The book is based on peer-review contributions and invited talks presented at the first International Workshop on MOdelling and Simulation of COmplex Systems for Sustainable Energy Efficiency, MOSCOSSEE 2021, held online on February 25-26, 2021, and organized by the LAboratory of Mechanics, Modelling and Production (LA2MP) from University of Sfax, Tunisia and the Department of Mechanical and Aeronautical engineering, Centre of Asset Integrity Management (C-AIM) from University of Pretoria, South Africa. By offering authoritative information on innovative methods and tools for application in renewable energy production, it provides a valuable resource to both academics and professionals, and a bridge to facilitate communication between the two groups.

This book illustrates how models of complex systems are built up and provides indispensable mathematical tools for studying their dynamics. This second edition includes more recent research results and many new and improved worked out examples and exercises.

Comprehension of complex systems comes from an understanding of not only the behavior of constituent elements but how they act together to form the behavior of the whole. However, given the multidisciplinary nature of complex systems, the scattering of information across different areas creates a chaotic situation for those trying to understand pos

This volume describes frontiers in social-behavioral modeling for contexts as diverse as national security, health, and on-line social gaming. Recent scientific and technological advances have created exciting opportunities for such improvements. However, the book also identifies crucial scientific, ethical, and cultural challenges to be met if social-behavioral modeling is to achieve its potential. Doing so will require new methods, data sources, and technology. The volume discusses these, including those needed to achieve and maintain high standards of ethics and privacy. The result should be a new generation of modeling that will advance science and, separately, aid decision-making on major social and security-related subjects despite the myriad uncertainties and complexities of social phenomena. Intended to be relatively comprehensive in scope, the volume balances theory-driven, data-driven, and hybrid approaches. The latter may be rapidly iterative, as when artificial-intelligence methods are coupled with theory-driven insights to build models that are sound, comprehensible and usable in new situations. With the intent of being a milestone document that sketches a research agenda for the next decade, the volume draws on the wisdom, ideas and suggestions of many noted researchers who draw in turn from anthropology, communications, complexity science, computer science, defense planning, economics, engineering, health systems, medicine, neuroscience, physics, political science, psychology, public policy and sociology. In brief, the volume discusses: Cutting-edge challenges and opportunities in modeling for social and behavioral science Special requirements for achieving high standards of privacy and ethics New approaches for developing theory while exploiting both empirical and computational data Issues of reproducibility, communication, explanation, and validation Special requirements for models intended to inform decision making about complex social systems

This book contains several contemporary topics in the areas of mathematical modelling and computation for complex systems. The readers find several new mathematical methods, mathematical models and computational techniques having significant relevance in studying various complex systems. The chapters aim to enrich the understanding of topics presented by carefully discussing the associated problems and issues, possible solutions and their applications or relevance in other scientific areas of study and research. The book is a valuable resource for graduate students, researchers and educators in understanding and studying various new aspects associated with complex systems. Key Feature • The chapters include theory and application in a mix and balanced way. • Readers find reasonable details of developments concerning a topic included in this book. • The text is emphasized to present in self-contained manner with inclusion of new research problems and questions.