Hybrid Computational Intelligent Systems by Bhattacharyya, Siddhartha;

Short description:

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.

Long description:

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.

Table of Contents:

Chapter 1

Creating ratings of agricultural universities based on their digital footprint

Mechatronic Complex’s Fuzzy System for Fixating Moving Objects

Quad Sensor-based Soil-Moisture Prediction using Machine Learning

Stability Analysis for a Diffusive Ratio-dependent Predator-prey Model involving two Delays

Analysis and Prediction of Physical Fitness Test Data of College Students Based on Grey Model

Analysis and Research on Book Borrowing Tendency Based on Apriori Algorithm

Performance Evaluation of Cargo Inspection Systems with the Function of Materials Recognition

Automated Medical Report Generation on Chest X-Ray Images using Co-Attention mechanism

An Energy Efficient Secured Arduino based Home Automation using Android Interface

A Multithreaded Android App to Notify Available `CoWIN’ Vaccination Slots to Multiple Recipients

Binary MMBAIS for Feature Selection Problem

Audio to Indian Sign Language Interpreter (AISLI) using Machine Translation and NLP Techniques

Fragile Medical Image Watermarking using Auto-generated Adaptive Key based Encryption

Designing of a Solution Model for Global Warming and Climate Change using Machine Learning and Data Engineering Techniques

Human Age Estimation using sit-to-stand exercise Data-driven Decision Making by Neural Network

Feature Based Suicide Ideation Detection from Twitter Data Using Machine Learning Techniques

Analyzing the role of Indian Media during the second wave of COVID using Topic Modeling

Hardware Efficient FIR Filter Design using Fast Converging Flower Pollination Algorithm - A Case Study of denoising PCG Signal

Voice Recognition System Using Deep Learning

Modified Harris Hawk Optimization Algorithm for Multi-level Image Thresholding

An automatic probabilistic framework for detection and segmentation of tumor in brain MRI images

Comparative Study of Generative Adversarial Networks for Sensor Data Generation based Remaining Useful Life Classification

Towards a Framework for Implementation of Quantum-Inspired Evolutionary Algorithm on Noisy Intermediate Scale Quantum Devices (IBMQ) for Solving Knapsack Problems