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

Format:

Book

Author/Creator:

Huang, Yo-Ping.

Contributor:

Wang, Wen-June.

Le, Hieu-Giang.

Hoang, An-Quoc.

Series:

Lecture Notes in Networks and Systems, 2367-3389 ; 1195

Language:

English

Subjects (All):

Computational intelligence.

Engineering--Data processing.

Engineering.

Energy policy.

Computational Intelligence.

Data Engineering.

Energy Policy, Economics and Management.

Local Subjects:

Computational Intelligence.

Data Engineering.

Energy Policy, Economics and Management.

Physical Description:

1 online resource (374 pages)

Edition:

1st ed. 2024.

Place of Publication:

Cham : Springer Nature Switzerland : Imprint: Springer, 2024.

Summary:

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.

Contents:

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.

Notes:

Description based on publisher supplied metadata and other sources.

Other Format:

Print version: Huang, Yo-Ping Computational Intelligence Methods for Green Technology and Sustainable Development

ISBN:

9783031761973

OCLC:

1490382756