Computational Intelligence Methods for Green Technology and Sustainable Development [electronic resource] : Proceedings of the International Conference GTSD2024, Volume 1 / edited by Yo-Ping Huang, Wen-June Wang, Hieu-Giang Le, An-Quoc Hoang.

Colaborador(es): Huang, Yo-Ping [editor.] | Wang, Wen-June [editor.] | Le, Hieu-Giang [editor.] | Hoang, An-Quoc [editor.] | SpringerLink (Online service)Tipo de material: TextoTextoSeries Lecture Notes in Networks and Systems ; 1195Editor: Cham : Springer Nature Switzerland : Imprint: Springer, 2024Edición: 1st ed. 2024Descripción: IX, 366 p. 188 illus., 159 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783031761973Tema(s): Computational intelligence | Engineering -- Data processing | Energy policy | Energy and state | Computational Intelligence | Data Engineering | Energy Policy, Economics and ManagementFormatos físicos adicionales: Printed edition:: Sin título; Printed edition:: Sin títuloClasificación CDD: 006.3 Clasificación LoC:Q342Recursos en línea: Libro electrónicoTexto
Contenidos:
Deep Learning For Commercial Building Load Forecasting: Hyperparameter Fine-tuning Convolution Neural Network-Multivariate Multilayered Long Short-term Memory Time-series Model -- Guided Multi-task Lane Line Detection with Road-object Semantic Segmentation -- Neuronal Networks for Visual Inspection of Assembly Completeness and Correctness in Manufacturing -- Person Detection for Monitoring Individuals Accessing the Robot Working Zones Using YOLOv8 -- Improvement of Small Object Detection Effectiveness based on Swin Transformer -- Dynamic Traffic Optimization System: Leveraging IoT and Fog Computing for Enhanced Urban Mobility with the RAO Algorithm -- Skeleton-based Posture Estimation for Human Action Recognition using Deep Learning -- Enhancing Cost-Efficient Image Captioning through ExpansionNet v2 Optimization -- Lite-GrSeg: Lightweight Architecture for 3D Point Cloud Road-Scene Semantic Segmentation -- Identifying Traffic Congestion through Vehicle Counting and Motion Estimation -- Improved Demand Forecasting Using Artificial Neural Networks: Incorporating Economy Indicators through Feature Construction -- A Novel Method for Ultrasonic Sensor Modeling Using Support Vector Regression -- Bearing Fault Diagnosis Framework based on Few-Shot Learning with Distribution Consistency and Structural Reparameterization -- Embedded Machine Learning for EMG-Based Elbow Motion Recognition -- Empirical Evaluation of Hybrid Time Series Forecasting Method between ARIMA and RBFNN under Parallel Model -- Research on Geometry-based Algorithm to Avoid Collisions With Pedestrians for Autonomous Vehicles -- Artificial Intelligence Application in Urban Space in The Light of The EU Data Protection -- Inverse Characterization of Multilayered Composite Plates using Ultrasonic Guided Waves and Machine Learning Algorithms -- Leveraging Big Data for Competitive Advantage in Entrepreneurship: A Decade Of Insights -- A New Adaptive Optimal Control using Non-conventional Prescribed Performance for Severe Disturbance System -- Novel Adaptive Model-Free Speed Control for Uncertain Permanent Magnet Synchronous Motor -- Optimizing Parameters of Direct Adaptive Neural Sliding Mode Controller for Coupled Tank System using MDE Optimization Algorithm -- Adaptive Fuzzy Controller for Ballbot With Complex Uncertainties -- A Computer Vision-based Eye-tracking System Toward An Eye-controlled Powered Wheelchair -- Adaptive Model Predictive Control (Adp_MPC) Utilized in Autonomous Vehicle (AV) Assistance Systems -- Observer-Based Path Following Control Method for Mobile Robots with An Event-Triggering Mechanism -- Advanced Event-Triggered Tracking Control Applied for Three-DOF Hover Unmanned Aerial Vehicle System -- LiDAR-Based Smart Navigation and Mapping for Mobile Robot on ROS -- Adaptive Formation Control of Underactuated Autonomous Underwater Vehicles with Multiple Constraints.
En: Springer Nature eBookResumen: This book is presented in two volumes, featuring peer-reviewed research papers from the 7th International Conference on Green Technology and Sustainable Development (GTSD), held in Ho Chi Minh City, Vietnam, from July 25 to 26, 2024. It highlights original research by experts from both academia and industry, centered on the theme of "Green Technology and Sustainable Development in the Industrial Revolution 4.0." The book underscores the critical importance of sustainability in education, technology, and economic development, while also showcasing the vital role of technological innovation in creating a greener future. The papers documented in this book cover a broad range of topics, including renewable energy systems, smart grids, artificial intelligence, robotics and intelligent systems, and computational intelligence, all with a focus on sustainable development, climate change mitigation, and environmental policy. These studies showcase cutting-edge technologies and innovative ideas related to green technology, offering actionable insights for advancing sustainable development across various sectors. The authors present research based on both experimental and numerical methods, offering solutions to current problems and optimizing existing methods. The insights and findings provided are valuable for industry experts, research institutions, universities, and anyone interested in advancing global sustainable development.
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Deep Learning For Commercial Building Load Forecasting: Hyperparameter Fine-tuning Convolution Neural Network-Multivariate Multilayered Long Short-term Memory Time-series Model -- Guided Multi-task Lane Line Detection with Road-object Semantic Segmentation -- Neuronal Networks for Visual Inspection of Assembly Completeness and Correctness in Manufacturing -- Person Detection for Monitoring Individuals Accessing the Robot Working Zones Using YOLOv8 -- Improvement of Small Object Detection Effectiveness based on Swin Transformer -- Dynamic Traffic Optimization System: Leveraging IoT and Fog Computing for Enhanced Urban Mobility with the RAO Algorithm -- Skeleton-based Posture Estimation for Human Action Recognition using Deep Learning -- Enhancing Cost-Efficient Image Captioning through ExpansionNet v2 Optimization -- Lite-GrSeg: Lightweight Architecture for 3D Point Cloud Road-Scene Semantic Segmentation -- Identifying Traffic Congestion through Vehicle Counting and Motion Estimation -- Improved Demand Forecasting Using Artificial Neural Networks: Incorporating Economy Indicators through Feature Construction -- A Novel Method for Ultrasonic Sensor Modeling Using Support Vector Regression -- Bearing Fault Diagnosis Framework based on Few-Shot Learning with Distribution Consistency and Structural Reparameterization -- Embedded Machine Learning for EMG-Based Elbow Motion Recognition -- Empirical Evaluation of Hybrid Time Series Forecasting Method between ARIMA and RBFNN under Parallel Model -- Research on Geometry-based Algorithm to Avoid Collisions With Pedestrians for Autonomous Vehicles -- Artificial Intelligence Application in Urban Space in The Light of The EU Data Protection -- Inverse Characterization of Multilayered Composite Plates using Ultrasonic Guided Waves and Machine Learning Algorithms -- Leveraging Big Data for Competitive Advantage in Entrepreneurship: A Decade Of Insights -- A New Adaptive Optimal Control using Non-conventional Prescribed Performance for Severe Disturbance System -- Novel Adaptive Model-Free Speed Control for Uncertain Permanent Magnet Synchronous Motor -- Optimizing Parameters of Direct Adaptive Neural Sliding Mode Controller for Coupled Tank System using MDE Optimization Algorithm -- Adaptive Fuzzy Controller for Ballbot With Complex Uncertainties -- A Computer Vision-based Eye-tracking System Toward An Eye-controlled Powered Wheelchair -- Adaptive Model Predictive Control (Adp_MPC) Utilized in Autonomous Vehicle (AV) Assistance Systems -- Observer-Based Path Following Control Method for Mobile Robots with An Event-Triggering Mechanism -- Advanced Event-Triggered Tracking Control Applied for Three-DOF Hover Unmanned Aerial Vehicle System -- LiDAR-Based Smart Navigation and Mapping for Mobile Robot on ROS -- Adaptive Formation Control of Underactuated Autonomous Underwater Vehicles with Multiple Constraints.

This book is presented in two volumes, featuring peer-reviewed research papers from the 7th International Conference on Green Technology and Sustainable Development (GTSD), held in Ho Chi Minh City, Vietnam, from July 25 to 26, 2024. It highlights original research by experts from both academia and industry, centered on the theme of "Green Technology and Sustainable Development in the Industrial Revolution 4.0." The book underscores the critical importance of sustainability in education, technology, and economic development, while also showcasing the vital role of technological innovation in creating a greener future. The papers documented in this book cover a broad range of topics, including renewable energy systems, smart grids, artificial intelligence, robotics and intelligent systems, and computational intelligence, all with a focus on sustainable development, climate change mitigation, and environmental policy. These studies showcase cutting-edge technologies and innovative ideas related to green technology, offering actionable insights for advancing sustainable development across various sectors. The authors present research based on both experimental and numerical methods, offering solutions to current problems and optimizing existing methods. The insights and findings provided are valuable for industry experts, research institutions, universities, and anyone interested in advancing global sustainable development.

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