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Multisource Data Integration and Comparative Analysis of Machine Learning Models For OnStreet Parking Prediction 2022 MDPI by naxcivanski25 is a document available to read on EtoBox.
What is Multisource Data Integration and Comparative Analysis of Machine Learning Models For OnStreet Parking Prediction 2022 MDPI about?
The article discusses the integration of multisource data for predicting on-street parking availability, highlighting the impact of external factors like pedestrian volume, weather, and traffic on prediction accuracy. A comparative analysis of various machine learning models revealed that Random Forest outperformed others with an accuracy of 81%. The proposed solution aims to enhance urban parking infrastructure, reduce congestion, and support smart city applications through real-time predictions.
- Author
- naxcivanski25
- Language
- EN