Intelligent Computing and Optimization

Name: Intelligent Computing and Optimization | Proceedings of the 6th International Conference on Intelligent Computing and Optimization 2023 (ICO2023), Volume 1
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Proceedings of the 6th International Conference on Intelligent Computing and Optimization 2023 (ICO2023), Volume 1

Pandian Vasant Mohammad Shamsul Arefin Vladimir Panchenko J. Joshua Thomas Elias Munapo Gerhard-Wilhelm Weber Roman Rodriguez-Aguilar(Editor)

Springer (Publisher)

Published on 10. November 2023

XVII, 348 pages

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978-3-031-36246-0 (ISBN)

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Content

Intro
Preface
Contents
About the Editors
Digital Transformation, Image Analysis and Sensor Technology
Digitally-Enabled Dynamic Capabilities for Digital Transformation
1 Introduction
2 Dynamic Capabilities for Digital Transformation
3 Methodology
4 Results and Analysis
5 Discussion and Conclusion
5.1 Implications for Theory
5.2 Implications for Practice
5.3 Limitations and Suggestions for Future Research
Appendix A: Robustness Test
Appendix B
References
Digitization of Feeding Processes in Pond Aquaculture Using a Cyber-Physical System for Analyzing Monitoring Data and Transmitting Information Using LoRaWAN Technology
1 Introduction
2 Data and Methods
3 Results and Discussion
4 Conclusion
References
Energy Efficient Routing Approaches in Wireless Sensor Networks: A Review
1 Introduction
2 Energy Consumption and Protocol Stacks
3 Related Work
3.1 Leach [5]
3.2 Leach-C [6]
3.3 Cluster Fuzzy-Based Algorithm [7]
3.4 Leach-Mac [8]
3.5 Energy-Aware Distributed Unequal Clustering [9]
3.6 Unequal Clustering Size Model [10]
3.7 Energy-Aware Distributed Clustering [11]
3.8 Fuzzy Based Balanced Cost CH Selection [12]
3.9 Distributed CH Scheduling [13]
3.10 K-means Based Clustering Algorithm [14]
3.11 Pareto Optimization Based Approach [15]
3.12 Energy Efficiency Semi Static Routing Algorithm [16]
3.13 Hybrid Energy Efficient Routing [17]
3.14 Improved ABC Algorithm [18]
3.15 Hierarchical Energy Balancing Multipath [19]
3.16 Novel Energy Aware Hierarchical Cluster Based Protocol [20]
3.17 Heuristic Algorithm for Clustering Hierarchy [21]
3.18 Multi-level Route Aware Clustering [22]
3.19 Double Phase Cluster Head Election Scheme [23]
4 Open Research Issues
5 Conclusion
References
Robust Vehicle Speed Estimation Based on Vision Sensor Using YOLOv5 and DeepSORT
1 Introduction
2 Related Works
2.1 Learning-Based
2.2 Three-Based Process
2.3 Speed Estimation
3 Proposed Method
3.1 Data Acquisition
3.2 Detection: YOLOv5
3.3 Tracking: DeepSORT
3.4 Speed Estimation
4 Conclusion
References
Automatic Alignment of Aerospace Images Based on the Search for Characteristic Points
1 Introduction
2 Materials and Methods
3 Conclusion
References
Method for Plant Leaves Square Area Estimation Based on Digital Image Analysis
1 Instruction
2 Methods and Materials
3 Results and Discussion
4 Conclusions
References
Digital Revolution Through Computational Intelligence: Innovative Applications and Trends
1 Introduction
2 The Five Main Principles of CI and Its Applications
2.1 Fuzzy Logic
2.2 Neural Networks
2.3 Evolutionary Computation
2.4 Learning Theory
2.5 Probabilistic Methods
2.6 Issues of Traditional Computing
3 Digital Revolution and Artificial Intelligence
4 Big Data
5 Artificial Intelligence (AI) and Computational Intelligence (CI)
6 Internet of Things (IoT) and Computational Intelligence (CI)
7 Computational Intelligence as a New Paradigm
8 Innovative Applications
9 Conclusion
References
Compressive Sensing and Orthogonal Matching Pursuit-Based Approach for Image Compression and Reconstruction
1 Introduction
2 Literature Review
3 Proposed Approach
4 Results
5 Conclusion
References
Capabilities for Digital Transformation and Sustainability in an Emerging Economy
1 Introduction
2 Capabilities for Digital Transformation and Sustainability
3 Research Methodology
4 Results and Analysis
5 Discussion and Conclusion
5.1 Implications for Theory and Practice
5.2 Limitations and Directions for Future Research
Appendix
References
Non-invasive Glucose Measurement with 940 nm Sensor Using Short Wave NIR Technique
1 Introduction
2 Proposed Methodology and Implementation
3 Mathematical Modelling for Prediction of Blood Glucose Concentration
4 Conclusion
References
Managing the Purchase-Sale Process of Digital Currencies Under Fuzzy Conditions
1 Introduction
2 Literature Review
3 The Purpose of the Study
4 Methods and Models
4.1 Model of Trading Operations with Cryptocurrencies in a Fuzzy Setting
4.2 The Solution of the Problem
5 Computational Experiment
6 Discussion of the Results of a Computational Experiment
7 Conclusions
References
A Comparative Analysis of the Impacts of Traditional and Digital Billing Methods
1 Introduction
2 Literature Review
3 Materials and Methods
3.1 Data Collection Methods
3.2 Participants
3.3 Data Analysis
3.4 Research Ethics
4 Results and Discussion
4.1 Experimental Result and Analysis
4.2 Discussion
4.3 Limitations and Future Works
5 Conclusion
References
Chest X-ray Image Classification Using Convolutional Neural Network to Identify Tuberculosis
1 Introduction
2 Related Work
3 System Architecture and Design
3.1 Dataset Description
3.2 Data Pre-processing
3.3 Model Architecture and Algorithms
4 Experimental Results
4.1 Experimental Setup
4.2 Experimental Result
4.3 Performance Evaluation
5 Conclusion
References
Digital Wireless Mini-transduce of Plant Thermoregulation
1 Introduction
2 Materials and Methods
3 Results and Discussion
4 Conclusion
References
Convolution Neural Network, Deep Learning, and Machine Learning
Effective Fault Prediction Techniques for the Green Cloud Computing Environment Applying Machine Learning to Enhance Network Management
1 Introduction
2 Literature Review
3 System Architecture and Design
3.1 Dataset Description
3.2 Pre-processing of Data Sources
4 Implementation and Experimental Result
4.1 Experimental Set-Up
4.2 Model Assessment
4.3 Performance Analysis
4.4 Result Analysis
5 Conclusion
References
Transforming the Financial Industry Through Machine and Deep Learning Innovations
1 Introduction
2 ML and DL Models
3 Literature Review
4 Application in Finance and the Way Forward
References
MRI-Based Brain Tumor Classification Using Various Deep Learning Convolutional Networks and CNN
1 Introduction
2 Related Work
3 System Architecture and Design
3.1 Description
3.2 Data Preprocessing
3.3 Proposed Model
3.4 Architecture and Design Proposed Model
4 Model Evaluation Result
4.1 Hypothetical Setup
4.2 Hypothetical Result
4.3 Confusion Matrix
4.4 Performance Evaluation
5 Conclusion
References
Deciphering Handwritten Text: A Convolutional Neural Network Framework for Handwritten Character Recognition
1 Introduction
2 Literature Review
3 Methodology
3.1 Dataset Description
4 Implementation
4.1 Device Set-Up
4.2 Implementation
5 Experimental Result
6 Conclusion
References
Applying Machine Learning Techniques to Forecast Demand in a South African Fast-Moving Consumer Goods Company
1 Introduction
2 Literature Review
3 Methodology and Data
3.1 Exploratory Data Analysis
3.2 Modeling
3.3 Accuracy Measures
4 Empirical Results
4.1 Exploratory Data Analysis
4.2 Demand Modeling
4.3 Moving Averages
4.4 SARIMA Model Results
4.5 Forecasting Using ANN Model
4.6 Model Accuracy
5 Conclusions
References
A Review on Machine Learning Algorithms for Cost Estimation in Construction Projects
1 Introduction
1.1 Cost Estimation Modelling Techniques
1.2 Machine Learning for Cost Estimation
1.3 Main Contribution
1.4 Paper Organization
2 Related Work
3 Open Research Challenges
4 Conclusion
References
A Computer Assisted Detection Framework of Kidney Diseases Based on CNN Model
1 Introduction
2 Background
3 Related Work
4 Materials and Methods
4.1 Dataset
4.2 Methodological Approach and Proposed Models
4.3 Pseudo Code
5 Experimental Result
5.1 Result
5.2 Performance Evaluation
6 Conclusion
References
Rice Blast Disease Detection Using CNN Models and DCGAN
1 Introduction
2 Related Work
3 Methodology
3.1 Dataset Preparation
3.2 Data Pre-processing
3.3 Network Architecture
4 Experimental Result and Discussion
5 Conclusion
References
Evaluation of Performance of Different Machine Learning Techniques for Structural Models
1 Introduction
2 The Prediction Methodologies
2.1 Support Vector Regression (SVR)
2.2 K-Nearest Neighbor (k-NN)
2.3 Bagging
3 Numerical Examples
3.1 Structural Models
3.2 Investigation of Prediction Models
4 Results
4.1 Prediction Performance and Error Measurements for Training Models
4.2 Prediction Performance and Error Measurements for Test Models
5 Conclusion
References
Age Estimation from Human Facial Expression Using Deep Neural Network
1 Introduction
2 Related Research
3 Materials and Proposed Methodology
3.1 CNN Architecture
3.2 Attention Module
3.3 Model Design and Tuning
4 Result and Observation
4.1 Dataset and Preprocessing
4.2 Augmentation Techniques
4.3 Performance Evaluation and Hyperparameters Tuning
5 Conclusion and Future Work
References
Recognition and Classification of Crop Images by Convolutional Neural Network of Hybrid Architecture
1 Introduction
2 Materials and Methods
3 Results and Discussion
4 Conclusion
References
A Comparative Study of Deep Learning Algorithms and SARIMA Models for Forecasting Monthly Solar Radiation and UV Index: Case Study for Mauritius
1 Introduction
2 Deep Learning Algorithms
2.1 Training of an ANN
3 Simulation Results and Discussions
3.1 Solar Radiation and UV Index Data
3.2 Result Analysis for Monthly Mean Solar Radiation and UV Index
4 Conclusions
References
A Study on Fault Classification and Location Using Supervised Machine Learning
1 Introduction
2 Classification of Faults
2.1 Shunt Faults (Short Circuit Faults)
3 Machine Learning Techniques
3.1 Supervised Machine Learning (SML)
3.2 Unsupervised Machine Learning (UML)
4 Related Work
5 Methodology
5.1 Test System and Data Base Generation
5.2 Algorithm
5.3 The Flow Chart
5.4 Results and Discussions
6 Conclusion
References
Deep Learning-Based Time Series Forecasting for CO2 Emission
1 Introduction
2 Literature Review
3 The Dataset
4 Methodology
4.1 Data Normalization
4.2 Sliding Window
4.3 Deep Learning Model-1 - Long Term-Short Memory
4.4 Deep Learning Model-2 - Convolutional Neural Network - Long Short-Term Memory
4.5 Deep Learning Model-3 - Dynamic Mode Decomposition (DMD) Using PyDMD
4.6 Analysis of Models Using Performance Evaluation Metrics
5 Results and Discussions
6 Conclusion
References
Manila City House Prices: A Machine Learning Analysis of the Current Market Value for Improvements
1 Introduction
2 Review of Related Literature
3 Methodology
3.1 Data Collection
3.2 Data Preprocessing
3.3 Model Training
3.4 Optimization
3.5 Model Evaluation
4 Results and Discussion
5 Conclusion
References
An Analysis of the Relationship Between Temperature Rise and GDP Using Machine Learning Techniques
1 Introduction
2 Method
3 Results and Discussion
4 Conclusion
References
Machine Learning Techniques for Predicting Remaining Useful Life (RUL) of Machinery for Sustainable Manufacturing Lines
1 Introduction
2 Literature Review
2.1 Machine Learning
2.2 Gradient Boosting Regression
3 Decision of Algorithm and Justification
4 Implementation
4.1 Predictive Model
5 Result and Discussion
References
Machine Learning-Based Predictive Modelling of Spot-Welding Process Parameters
1 Introduction
2 Machine Learning Algorithms
2.1 Linear Regression
2.2 Random Forest Regression
2.3 Adaptive Boosting Regression
2.4 SVM Regression
3 Predictive Model Performance Evaluation Metrics
4 Results and Discussion
4.1 Case Study: Spot Welding
4.2 Effect of Process Parameters
4.3 ML Modelling of Nugget Diameter (ND)
4.4 ML Modelling of Nugget Height (NH)
5 Conclusions
References
Author Index

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Intelligent Computing and Optimization

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