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Intelligent Computing and Optimization : Proceedings of the 6th International Conference on Intelligent Computing and Optimization 2023 (ICO2023), Volume 1 / / edited by Pandian Vasant, Mohammad Shamsul Arefin, Vladimir Panchenko, J. Joshua Thomas, Elias Munapo, Gerhard-Wilhelm Weber, Roman Rodriguez-Aguilar



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Autore: Vasant Pandian Visualizza persona
Titolo: Intelligent Computing and Optimization : Proceedings of the 6th International Conference on Intelligent Computing and Optimization 2023 (ICO2023), Volume 1 / / edited by Pandian Vasant, Mohammad Shamsul Arefin, Vladimir Panchenko, J. Joshua Thomas, Elias Munapo, Gerhard-Wilhelm Weber, Roman Rodriguez-Aguilar Visualizza cluster
Pubblicazione: Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Edizione: 1st ed. 2023.
Descrizione fisica: 1 online resource (364 pages)
Disciplina: 006.3
Soggetto topico: Computational intelligence
Artificial intelligence
Computational Intelligence
Artificial Intelligence
Altri autori: Shamsul ArefinMohammad  
PanchenkoVladimir  
ThomasJ. Joshua  
MunapoElias  
WeberGerhard-Wilhelm  
Rodriguez AguilarRoman  
Nota di contenuto: 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.
Sommario/riassunto: This book of Springer Nature is another proof of Springer’s outstanding greatness on the lively interface of Holistic Computational Optimization, Green IoTs, Smart Modeling, and Deep Learning! It is a masterpiece of what our community of academics and experts can provide when an interconnected approach of joint, mutual, and meta-learning is supported by advanced operational research and experience of the World-Leader Springer Nature! The 6th edition of International Conference on Intelligent Computing and Optimization took place at G Hua Hin Resort & Mall on April 27–28, 2023, with tremendous support from the global research scholars across the planet. Objective is to celebrate “Research Novelty with Compassion and Wisdom” with researchers, scholars, experts, and investigators in Intelligent Computing and Optimization across the globe, to share knowledge, experience, and innovation—a marvelous opportunity for discourse and mutuality by novel research, invention, and creativity. This proceedings book of the 6th ICO’2023 is published by Springer Nature—Quality Label of Enlightenment. .
Titolo autorizzato: Intelligent Computing and Optimization  Visualizza cluster
ISBN: 9783031362460
3031362462
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910763592003321
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Serie: Lecture Notes in Networks and Systems, . 2367-3389 ; ; 729