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Hybrid Computational Intelligent Systems: Modeling, Simulation and Optimization

LeeAndro

Trusted Editor
Trusted Editor
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English | 2023 | ISBN: 9781003381167 | 397 pages | True PDF | 30.99 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- 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

strats to evolve robust and failsafe intelligent system modeling

and simulation.

The volume also highlights novel applications for different eeering

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 eeering 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- hybrid intelligent systems is a prerequisite

for deriving any real-life system solution.

Optimized system modeling and simulation enable real- and failsafe

operations of the existing hybrid intelligent system solutions.

Information presented in an accessible way for researchers, eeers,

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- data-intensive intelligent systems.



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