Hybrid Computational Intelligent Systems
CRC Press (Verlag)
978-1-032-39302-5 (ISBN)
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.
Siddhartha Bhattacharyya is currently serving as the Principal of Rajnagar Mahavidyalaya, Rajnagar, Birbhum, India. He has been inducted into the People of ACM hall of fame by ACM, the USA in 2020. He has been elected as a full foreign member of the Russian Academy of Natural Sciences. He has been elected as a full fellow of The Royal Society for Arts, Manufactures and Commerce (RSA), London, UK. He is a co-author of 6 books and the co-editor of 75 books and has more than 300 research publications in international journals and conference proceedings to his credit. His research interests include hybrid intelligence, pattern recognition, multimedia data processing, social networks, and quantum computing.
Chapter 1
Creating ratings of agricultural universities based on their digital footprint
Chapter 2
Mechatronic Complex’s Fuzzy System for Fixating Moving Objects
Chapter 3
Quad Sensor-based Soil-Moisture Prediction using Machine Learning
Chapter 4
Stability Analysis for a Diffusive Ratio-dependent Predator-prey Model involving two Delays
Chapter 5
Analysis and Prediction of Physical Fitness Test Data of College Students Based on Grey Model
Chapter 6
Analysis and Research on Book Borrowing Tendency Based on Apriori Algorithm
Chapter 7
Performance Evaluation of Cargo Inspection Systems with the Function of Materials Recognition
Chapter 8
Automated Medical Report Generation on Chest X-Ray Images using Co-Attention mechanism
Chapter 9
An Energy Efficient Secured Arduino based Home Automation using Android Interface
Chapter 10
A Multithreaded Android App to Notify Available `CoWIN’ Vaccination Slots to Multiple Recipients
Chapter 11
Binary MMBAIS for Feature Selection Problem
Chapter 12
Audio to Indian Sign Language Interpreter (AISLI) using Machine Translation and NLP Techniques
Chapter 13
Fragile Medical Image Watermarking using Auto-generated Adaptive Key based Encryption
Chapter 14
Designing of a Solution Model for Global Warming and Climate Change using Machine Learning and Data Engineering Techniques
Chapter 15
Human Age Estimation using sit-to-stand exercise Data-driven Decision Making by Neural Network
Chapter 16
Feature Based Suicide Ideation Detection from Twitter Data Using Machine Learning Techniques
Chapter 17
Analyzing the role of Indian Media during the second wave of COVID using Topic Modeling
Chapter 18
Hardware Efficient FIR Filter Design using Fast Converging Flower Pollination Algorithm - A Case Study of denoising PCG Signal
Chapter 19
Voice Recognition System Using Deep Learning
Chapter 20
Modified Harris Hawk Optimization Algorithm for Multi-level Image Thresholding
Chapter 21
An automatic probabilistic framework for detection and segmentation of tumor in brain MRI images
Chapter 22
Comparative Study of Generative Adversarial Networks for Sensor Data Generation based Remaining Useful Life Classification
Chapter 23
Towards a Framework for Implementation of Quantum-Inspired Evolutionary Algorithm on Noisy Intermediate Scale Quantum Devices (IBMQ) for Solving Knapsack Problems
| Erscheinungsdatum | 17.04.2023 |
|---|---|
| Reihe/Serie | Quantum Machine Intelligence |
| Zusatzinfo | 79 Tables, black and white; 223 Halftones, black and white; 223 Illustrations, black and white |
| Verlagsort | London |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Gewicht | 793 g |
| Themenwelt | Informatik ► Grafik / Design ► Digitale Bildverarbeitung |
| Technik ► Elektrotechnik / Energietechnik | |
| Technik ► Umwelttechnik / Biotechnologie | |
| ISBN-10 | 1-032-39302-5 / 1032393025 |
| ISBN-13 | 978-1-032-39302-5 / 9781032393025 |
| Zustand | Neuware |
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