Hybrid Computational Intelligent Systems: Modeling, Simulation and Optimization

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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.

Author(s): Siddhartha Bhattacharyya
Series: Quantum Machine Intelligence
Publisher: CRC Press
Year: 2023

Language: English
Pages: 396
City: Boca Raton

Cover
Half Title
Series Page
Title Page
Copyright Page
Dedication
Table of Contents
Preface
Editors
Contributors
1 Creating Ratings of Agricultural Universities based on their Digital Footprint
1.1 Introduction
1.2 Methodology for the Formation of University Rankings Based on the Passive Digital Footprint
1.3 Methodology for Generating Rating Based On a Semi-Active Digital Footprint
1.4 Methodology for Generating Ratings Based on an Active Digital Footprint
1.5 Rating Calculation Results
1.6 Conclusion
References
2 Mechatronic Complex’s Fuzzy System for Fixating Moving Objects
2.1 Introduction
2.2 Composition and Principle of Operation of the MC
2.3 Kinematic Model of the MC
2.4 Fuzzy SISO-system
2.4.1 Fuzzification
2.4.2 Input and output Membership Functions
2.4.3 Defuzzification
2.5 Experimental Research
2.6 Conclusions
References
3 Quad Sensor-based Soil-moisture Prediction using Machine Learning
3.1 Introduction
3.2 Related Works
3.3 Proposed System
3.3.1 Sensors used in the Proposed Framework
3.3.2 Hardware Architecture
3.3.3 Dataset
3.3.4 Data Analysis
3.3.5 Performance Evaluation Measures
3.4 Results and Discussion
3.5 Conclusion
References
4 Stability Analysis for a Diffusive Ratio-dependent Predator-prey Model Involving Two Delays
4.1 Introduction
4.2 Stability Analysis
4.3 Examples and Simulations
4.4 Conclusion
Acknowledgment
References
5 Analysis and Prediction of Physical Fitness test Data of College Students based on Grey Model
5.1 Introduction
5.2 Grey Model Related Theories
5.2.1 Introduction to the Grey Model
5.2.2 Grey GM (1,1) Prediction Model Algorithm
5.2.3 Grey Forecasting Model Accuracy Test
5.3 Analysis and Prediction of Physique Based on Grey Model
5.3.1 Data Preprocessing
5.3.2 Data Analysis of Student Fitness Test
5.3.3 Prediction of Student Physical test data Based on Grey Model
5.3.4 Prediction of Physique Development Trend based on Grey Model
5.4 Conclusion
Acknowledgment
References
6 Analysis and Research on Book Borrowing Tendency based on Apriori Algorithm
6.1 Introduction
6.2 Relevant Theories
6.2.1 Association Rules
6.2.2 Apriori Algorithm
6.3 Analysis of Book Borrowing Data based on Apriori Algorithm
6.3.1 Data Preprocessing
6.3.2 Description and Analysis of Influencing Factors of book Borrowing Volume
6.3.2.1 Relationship Between Book Types and book Borrowing
6.3.2.2 Relationship Between Grade and book Borrowing
6.3.2.3 Relationship between time Period and book Borrowing
6.3.2.4 Relationship between College and book Borrowing
6.3.2.5 Relationship Between Major and book Borrowing
6.3.2.6 Borrowing Preference
6.3.3 Implementation of Apriori Algorithm based on Python
6.3.4 Visualization of Apriori Model
6.3.5 Evaluation and Application of Borrowing Data Tendency
6.4 Conclusion
Acknowledgment
References
7 Performance Evaluation of Cargo Inspection: Systems with the Function of Materials Recognition
7.1 Introduction
7.2 Key Parameters and Features of High Energy IS with Material Recognition
7.3 Mathematical Model of IS with Dual Energy Recognition of Materials
7.4 Performance Estimation of IS with Material Recognition
7.5 Conclusions and Results
References
8 Automated Medical Report Generation on Chest X-ray: Images using Co-attention Mechanism
8.1 Introduction
8.2 Materials and Methods
8.2.1 Dataset
8.2.2 Experimental Setup
8.2.2.1 Natural Language Processing (NLP) Pipeline
8.2.2.2 Convolutional neural Network
8.2.2.3 Recurrent Neural Network
8.2.2.4 Sequence-to-sequence Model with Co-attention Mechanism
8.3 Results and Discussion
8.4 Conclusions and Future Works
References
9 An Energy-efficient Secured Arduino-based Home Automation using Android Interface
9.1 Introduction
9.2 Literature Review
9.3 System Architecture
9.3.1 Experimental Devices
9.3.1.1 RFID-RC522 Module
9.3.1.2 Servomotor
9.3.1.3 Arduino UNO
9.3.1.4 Bluetooth HC05 Module
9.3.1.5 Relay Switch
9.3.1.6 Android System
9.3.2 Process Diagram
9.4 Result and Discussion
9.4.1 Experimental Setup
9.4.2 Performance Analysis
9.5 Conclusion
References
10 A Multithreaded Android App to Notify Available ‘CoWIN’ Vaccination Slots to Multiple Recipients
10.1 Introduction
10.2 Related Works
10.3 Detailed Description of Application
10.3.1 Functional Features
10.3.2 User Feedback Module
10.3.3 APIs Used in this Application
10.3.4 Design Descriptions
10.4 Advantages of ‘Amar Protishedhak Bondhu’
10.5 Usability Analysis
10.6 Conclusions and Future Scopes
References
11 Binary MMBAIS for Feature Selection Problem
11.1 Introduction: Feature Selection and Metaheuristic Algorithm
11.2 Related Work
11.3 MMBAIS Algorithm
11.4 Binary MMBAIS
11.4.1 Objective Function
11.4.2 Structure of Binary MMBAIS
11.5 Methodology
11.6 Experimental Setup
11.6.1 Datasets
11.6.2 Classification Methods
11.7 Result and Performance Analysis
11.8 Conclusion
References
12 Audio to Indian Sign Language Interpreter (AISLI) using Machine Translation and NLP Techniques
12.1 Introduction
12.2 Literature Review
12.3 Speech Recognition
12.3.1 Google API
12.3.2 Sign Language
12.3.3 Indian Sign Language (ISL) and Alphabets
12.4 Implementing ISL in AISLI
12.4.1 AISLI Demonstration
12.5 Conclusions
References
13 Fragile Medical Image Watermarking using Auto-generated Adaptive Key-based Encryption
13.1 Introduction
13.2 Proposed Methodology
13.2.1 Watermark Embedding
13.2.2 Extraction of Watermark and EPR
13.3 Results and Discussion
13.4 Conclusion
References
14 Designing of a Solution Model for Global Warming and Climate Change using Machine Learning and data Engineering Techniques
14.1 Introduction
14.2 Related Work
14.3 Solution Technique
14.3.1 Prediction Technique Selection
14.4 Solution Architecture
14.5 Result and Analysis
14.6 Conclusion
References
15 Human age Estimation using Sit-to-stand Exercise Data-driven Decision-making by Neural Network
15.1 Introduction
15.2 Literature Review
15.2.1 Motivation
15.2.1.1 Specific Contribution
15.3 Methodology
15.4 Results and Discussion
15.5 Conclusions and Future Scope
References
16 Feature-based Suicide-ideation Detection from Twitter Data using Machine Learning Techniques
16.1 Introduction
16.2 Related Work
16.3 Proposed Methodology
16.3.1 Data Set Exploration and Preparation
16.3.2 Feature Extraction and Analysis
16.4 Empirical Evaluation
16.4.1 Classification Model
16.4.2 Classification Results
16.5 Conclusion and Future Scope
References
17 Analyzing the Role of Indian Media during the Second wave of COVID using Topic Modeling
17.1 Introduction
17.2 Literature Survey
17.3 Methodology
17.3.1 Data Collection
17.3.2 Data Pre-processing
17.3.3 Topic Modeling
17.4 Results and Discussion
17.5 Conclusion
References
18 Hardware-efficient FIR Filter Design using fast Converging flower Pollination Algorithm – A case Study of Denoising PCG Signal
18.1 Introduction
18.2 Problem Formulations
18.2.1 Specification of Desired Filter Characteristics
18.2.2 Filter Coefficients Computation
18.2.3 Design filter Architecture
18.3 Hardware-efficient FIR Filter Design using fast Convergingflower Pollination Algorithm
18.3.1 Flower Pollination Algorithm
18.3.2 Fast Converging Flower Pollination Algorithm
18.4 Simulation Results
18.5 Case Study
18.6 Conclusions
Bibliography
19 Voice Recognition System using Deep Learning
19.1 Introduction
19.2 Related Works
19.3 Dataset
19.4 Methods
19.4.1 Detection and Fine-tuning
19.4.2 Finding the Optimal Window Size
19.4.3 Training the Model
19.5 Results and Analysis
19.6 Conclusions
References
20 Modified Harris Hawk Optimization Algorithm for Multilevel image Thresholding
20.1 Introduction
20.2 Harris’ Hawks Optimization
20.3 Quantitative Evaluation Measure
20.3.1 Modified Otsu
20.3.2 Entropy Yen
20.4 Proposed Methodology
20.4.1 Exploration Phase
20.4.2 Transition from Exploration to Exploitation Phase
20.4.3 Exploitation Phase
20.5 Experimental Results
20.5.1 Details of the Experimental Data
20.5.2 Performance Measures
20.5.3 Results
20.6 Conclusion and Future Direction
References
21 An Automatic Probabilistic Framework for Detection and Segmentation of Tumor in brain MRI Images
21.1 Introduction
21.2 Related Work
21.3 Proposed Framework and Methodology
21.4 Results and Discussion
21.5 Conclusion
References
22 Comparative Study of Generative Adversarial Networks for Sensor data Generation-based Remaining Useful life Classification
22.1 Introduction and Motivation
22.2 Related Work
22.3 Proposed Technique
22.4 Research Methodology
22.5 Experimental Setup
22.6 Result and Discussion
22.7 Conclusion
References
23 Toward a Framework for Implementation of Quantum-inspired Evolutionary Algorithm on Noisy Intermediate Scale Quantum Devices (IBMQ) for Solving Knapsack Problems
23.1 Introduction
23.2 Overview
23.2.1 Motivation
23.2.2 Knapsack Problem
23.2.3 QIEA
23.2.4 QIEA for Knapsack
23.3 Adaptation of EA on IBMQ
23.3.1 Quantum Routine
23.3.2 Quantum Circuit
23.3.3 Proposed Methodology
23.4 Framework and Experimentation Parameters
23.4.1 Framework
23.4.2 Experimentation
23.5 Results
23.5.1 Readings
23.5.2 Graphical Representation
23.5.3 Time Evaluation
23.5.4 Evaluation of Results
23.6 Conclusion
Notes
Bibliography
Index