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.
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.
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.
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.
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