Название: Hybrid Computational Intelligent Systems: Modeling, Simulation and Optimization
Автор: Siddhartha Bhattacharyya
Издательство: CRC Press
Серия: Quantum Machine Intelligence
Год: 2023
Страниц: 397
Язык: английский
Формат: pdf (true)
Размер: 28.6 MB

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, human factors, along with the enhancement of the existing state-of-art in a high-performance computing setup. In addition, the book presents optimization strategies to evolve robust and failsafe intelligent system modeling and simulation. The volume also highlights novel applications to different engineering problems including signal and data processing, speech, image, sensor data processing, innovative intelligent systems and swarm intelligent manufacturing systems.

Almost every technological innovation in the present times is being driven by intelligence in one form or the other with the advent of Computational Intelligence. Computational Intelligence has made its presence felt in every nook and corner of the world, thanks to the rapid exploration of research in this direction. Computational Intelligence is now not limited to only specific computational fields; it has made giant strides into several interdisciplinary fields of science, engineering, medical science, business, and finance including signal processing, smart manufacturing, predictive control, robot navigation, smart cities, sensor design to name a few. Latest advances in evolving soft computing concepts and algorithms toward enabling intelligent solutions to real-life problems have enriched this field of Computational Intelligence. To add to this, researchers have conjoined different intelligent tools and techniques to evolve hybrid intelligent systems, which results in more efficient alternatives to stand-alone intelligent systems.

This volume comprises 23 well-versed contributory chapters entailing different facets of intelligent system modeling and their applications to a wide variety of data- and information-intensive frameworks.

Presently, Internet of Things (IoT) is one of the ways of reducing manual intervention in different domains such as smart appliances and smart detection systems. Smart appliances are widely used technology that can be used in many areas such as in our home or office for providing comfort, energy consumption, security, etc. Such kind of system has become an important and integral part of the modern home automation system. However, there exist some problems such as dedicated interfacing, user authentication, high security, and other related factors. To address these problems, the authors develop a low-power smart home automation system in Chapter 9, which not only controls the home appliances but also increases the security of the entire system. In this work, smart appliances can be easily controlled by using a smartphone. The proposed system and its hardware are based on Arduino with its interface and communication via Bluetooth with peripheral devices and the Android device system. The security and authentication of the system are done through RFID. The efficacy of the proposed system has been judged with respect to reduced time delay, power consumption,
and security.

Features:

A self-contained approach to integrating the principles of hybrid computational intelligence 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.