This book creates the emergence of disruptive technologies that have led to a significant change in the role of mathematics and statistics for problem solving, with the use of sophisticated software and hardware in solving complex systems and process. In the era of digital technology, mathematics and statistics need to be highly relevant to be able to cater for the needs of IR4.0 such as big data analytics, simulation, autonomous system, and cloud computing. Motivated by this development, a total of 26 chapters are contributed by respectable experts for this book. The main scope of the book is to conduct a new system of modeling and simulations on solving differential equations, nonlinear equations, energy, epidemiology, and risk assessment. This book is of interest for postgraduate students, researchers as well as other scientists who are working in numerical modeling and simulations based on efficient mathematical and statistical techniques.

This book develops a new system of modeling and simulations based on intelligence system. As we are directly moving from Third Industrial Revolution (IR3.0) to Fourth Industrial Revolution (IR4.0), there are many emergence techniques and algorithm that appear in many sciences and engineering branches. Nowadays, most industries are using IR4.0 in their product development as well as to refine their products. These include simulation on oil rig drilling, big data analytics on consumer analytics, fastest algorithm for large-scale numerical simulations and many more. These will save millions of dollar in the operating costs. Without any doubt, mathematics, statistics and computing are well blended to form an intelligent system for simulation and modeling. Motivated by this rapid development, in this book, a total of 41 chapters are contributed by the respective experts. The main scope of the book is to develop a new system of modeling and simulations based on machine learning, neural networks, efficient numerical algorithm and statistical methods. This book is highly suitable for postgraduate students, researchers as well as scientists that have interest in intelligent numerical modeling and simulations.

Providing a thorough introduction to the field of soft computing techniques, Intelligent Systems: Modeling, Optimization, and Control covers every major technique in artificial intelligence in a clear and practical style. This book highlights current research and applications, addresses issues encountered in the development of applied systems, and describes a wide range of intelligent systems techniques, including neural networks, fuzzy logic, evolutionary strategy, and genetic algorithms. The book demonstrates concepts through simulation examples and practical experimental results. Case studies are also presented from each field to facilitate understanding.

This book continues the previous edition: Samsul Ariffin Abdul Karim (2022). Intelligent Systems Modeling and Simulation II: Machine Learning, Neural Networks, Efficient Numerical Algorithm and Statistical Methods, Studies in Systems, Decision and Control (SSDC, volume 444, 22k Access). After two years, Intelligent Systems Modeling and Simulation have evolved tremendously through the latest and advanced emergence technologies and many highly sophisticated algorithms have been developed by blending artificial intelligence (AI) and mathematics, statistics, data modelling and other related research areas. These blends offer many opportunities and further investigations into the overlapand equality between these areas. It is a well-known fact that most industries and companies have utilized this IR4.0 architecture in various levels of manufacturing and decision processes. Besides, nowadays IR5.0 or Society5.0 has also been embedded into various systems in industries as well as in Teaching and Learning (TL). The combination of IR4.0 and Society 5.0 may result in more impactful outcomes, especially in automated decision-making and reliable simulations-based modelling. Furthermore, IR4.0 and Society5.0 through Data-Driven have made a significant contribution to the government and companies to analyse big data via predictive analytics. Cyber security firewalls on all systems must be up to date to prevent any malicious attacks by hackers. Otherwise, our citizens might be scammed and according to NBC News, the total loss for 2022 is around USD 8.8 billion. These are very huge amount. Just recently, COVID-19 has been spreading all over the world again. To assist the Ministry of Health (MOH) and other government agencies, it is very crucial to identify, predict, detect and quarantine the COVID-19 on the susceptible persons soonest possible. Intelligent Image Processing techniques are very demanding here. This is to ensure that we can control and minimise the spread. Inspire by these latest developments, in this book, various experts in the areas of Artificial Intelligence, Machine Learning, Deep Learning, Neural Networks, Modeling and Simulation, Cyber Security and Awareness, Intelligent Statistical Methods, Big Data Analytics, Sentiment Analytics, Intelligent Function Approximation, Image Processing in medical imaging especially on COVID-19, AI in Teaching and Learning, and Computational Intelligence will share their latest studies and experiences. Their finding is in line with United Nations Sustainable Development Goals (SDGs) such as No. 9: Industry, Innovation, and Infrastructure, particularly Target 9.4, 9.5, 9.a, 9.b and 9.c, No. 11: Sustainable Cities and Communities particularly Target 11.b and Indicators 11.b.1 and 11.b.2, and SDG No. 4: Quality Education; particularly Target 4.7 and Indicator 4.7.1. This book is highly suitable for postgraduate students and researchers to get the state-of-the-art current research directions as well as for the scientists that have an interest and working in intelligent numerical modelling and simulations through AI, Machine Learning, Neural Networks, and its related counterparts.

Mathematical Modeling for Intelligent Systems: Theory, Methods, and Simulation aims to provide a reference for the applications of mathematical modeling using intelligent techniques in various unique industry problems in the era of Industry 4.0. Providing a thorough introduction to the field of soft-computing techniques, this book covers every major technique in artificial intelligence in a clear and practical style. It also highlights current research and applications, addresses issues encountered in the development of applied systems, and describes a wide range of intelligent systems techniques, including neural networks, fuzzy logic, evolutionary strategy, and genetic algorithms. This book demonstrates concepts through simulation examples and practical experimental results. Key Features: • Offers a well-balanced mathematical analysis of modeling physical systems • Summarizes basic principles in differential geometry and convex analysis as needed • Covers a wide range of industrial and social applications and bridges the gap between core theory and costly experiments through simulations and modeling • Focuses on manifold ranging from stability of fluid flows, nanofluids, drug delivery, and security of image data to pandemic modeling, etc. This book is primarily aimed at advanced undergraduates and postgraduate students studying computer science, mathematics, and statistics. Researchers and professionals will also find this book useful.

The International Council on Systems Engineering (INCOSE) defines Systems Engineering as an interdisciplinary approach and means to enable the realization of successful systems. Researchers are using intelligence-based techniques to support the practices of systems engineering in an innovative way. This research volume includes a selection of contributions by subject experts to design better systems.

Hybrid Computational Intelligent Systems – Modeling, Simulation and Optimization unearths the latest advances in evolving hybrid intelligent modeling and simulation of human-centric data-intensive applications optimized for real-time use, thereby enabling researchers to come up with novel breakthroughs in this ever-growing field. Salient features include the fundamentals of modeling and simulation with recourse to knowledge-based simulation, interaction paradigms, and human factors, along with the enhancement of the existing state of art in a high-performance computing setup. In addition, this book presents optimization strategies to evolve robust and failsafe intelligent system modeling and simulation. The volume also highlights novel applications for different engineering problems including signal and data processing, speech, image, sensor data processing, innovative intelligent systems, and swarm intelligent manufacturing systems. Features: A self-contained approach to integrating the principles of hybrid computational ntelligence with system modeling and simulation Well-versed foundation of computational intelligence and its application to real life engineering problems Elucidates essential background, concepts, definitions, and theories thereby putting forward a complete treatment on the subject Effective modeling of hybrid intelligent systems forms the backbone of almost every operative system in real-life Proper simulation of real-time hybrid intelligent systems is a prerequisite for deriving any real-life system solution Optimized system modeling and simulation enable real-time and failsafe operations of the existing hybrid intelligent system solutions Information presented in an accessible way for researchers, engineers, developers, and practitioners from academia and industry working in all major areas and interdisciplinary areas of hybrid computational intelligence and communication systems to evolve human-centered modeling and simulations of real-time data-intensive intelligent systems.