Description
Book Synopsis.- Smart and Intelligent Transportation Systems.
.- Optimizing Traffic Flow: A Multi-Agent Approach to Dynamic Signal Control Accounting for Vehicle Types.
.- Estimating Parking Lot Occupancy Based on Traffic Congestion for Route Planning.
.- A Framework for Simulating the Optimal Allocation of Shared E-Scooters.
.- Performance Enhancement of Two-Way DF Relayed Cooperative NOMA Vehicular Network with Outdated CSI and Imperfect SIC.
.- Machine/Deep/Reinforcement Learning in Industries.
.- Integration of Artificial Intelligence for the Analysis and Monitoring of Projects within Companies.
.- Multi-Criteria Inventory Classification with Machine Learning Algorithms in the Manufacturing Industry.
.- Analyzing Results of Business Process Automation with Machine Learning Methods.
.- Predictive Analysis of Surface Defects in Engineering Structures Using Machine Learning Technologies.
.- Enhancing Autonomous Industrial Navigation: Deep Reinforcement Learning for Obstacle Avoidance in Challenging Environments.
.- Fast and Accurate Right-Hand Detection Based on YOLOv8 from the Egocentric Vision Dataset.
.- Comparative Study of 3D Hand Pose Estimation on HOI4D Dataset by Convolutional Neural Networks.
.- Prediction of Ethereum Prices Based on Blockchain Information in an Industrial Finance System using Machine Learning Techniques.
.- Email Classification of Text Data Using Machine Learning and Natural Language Processing Technique.
.- The Fake News Detection Model Explanation and Infrastructure Aspects.
.- Advances of Artificial Intelligence/Operational Research Tools in Healthcare.
.- An Advanced Approach to COVID-19 Detection using Deep Learning and X-ray Imaging.
.- Exploring Factors that Affect the User Intention to Take Covid Vaccine Dose.
.- Unsupervised Incremental-Decremental Attribute Learning Healthcare Application based Feature Selection.
.- On Solving the Physicians Scheduling Problem at an Emergency Department: A Case Study from Canada.
.- Temporal Emotional and Thematic Progression (TETP): A Novel Analysis of Mental Health Discussions on Social Platforms.
