A Novel Spatial–Temporal Deep Learning Method for Metro Flow Prediction Considering External Factors and Periodicity

B Shi, Z Wang, J Yan, Q Yang, N Yang - Applied Sciences, 2024 - mdpi.com
Predicting metro traffic flow is crucial for efficient urban planning and transit management. It
enables cities to optimize resource allocation, reduce congestion, and enhance the overall …

Short-Term Bus Passenger Flow Prediction Based on BiLSTM Neural Network

X Zhou, Q Wang, Y Zhang, B Li… - Journal of Transportation …, 2025 - ascelibrary.org
In order to analyze the passenger flow characteristics of single line bus and improve the
operation of public transportation vehicles through combination optimization, this paper …

DA-RNN-Based Bus Arrival Time Prediction Model

Z Li - … Journal of Intelligent Transportation Systems Research, 2024 - Springer
Accurate prediction of bus arrival time is crucial for constructing smart cities and intelligent
transportation systems. Objectivity and clarity must be maintained throughout to ensure …

COMPARISON OF MACHINE LEARNING TECHNIQUES FOR CLASSIFICATION OF DISTRIBUTED DENIAL OF SERVICE ATTACKS BASED ON FEATURE …

MI Rizaldi, DR Chandranegara… - JIPI (Jurnal …, 2024 - jurnal.stkippgritulungagung.ac.id
Abstract Distributed Denial-of-Service (DDoS) attacks present a noteworthy cybersecurity
hazard to software-defined networks (SDNs). This investigation presents an approach that …