Traffic speed prediction has implications for urban planning, congestion reduction, and intelligent control systems. To maintain a uniform traffic speed and to avoid issues related to traffic, an accurate traffic speed forecast can help in supplying significant information. The capacity to forecast short-term traffic speed is a fundamental part of both Intelligent Transportation System (ITS) and the Internet of Vehicles (IoV). To achieve better accuracy in predicting short-term traffic speed, we introduced a GSA-Bi-LSTM model by optimizing the Bi-directional Long Short-Term Memory (Bi-LSTM) network prediction framework with Gravitational Search Algorithm (GSA) due to its features of fast convergence, great reliability and significant global search ability of parameters. The utilization of the GSA optimization technique is employed to optimize the hyperparameters of the Bi-LSTM model. By making use of the bidirectional properties of Bi-LSTM layers, the model’s architecture aims to enhance prediction accuracy and effectively capture the intricate patterns present in the input data. From the analysis of the experimental results, it becomes evident that the convenience provided by our proposed GSA-Bi-LSTM model surpasses that of conventional models in terms of evaluation metrics. Additionally, it is also noted that GSA has superior optimization capabilities than Particle Swarm Optimization (PSO) in terms of optimizing the Bi-LSTM approach for traffic speed forecasting.
Bi-directional Long Short Term Memory Neural Network for Short-Term Traffic Speed Prediction Using Gravitational Search Algorithm
Int. J. ITS Res.
International Journal of Intelligent Transportation Systems Research ; 22 , 2 ; 316-327
2024-08-01
12 pages
Article (Journal)
Electronic Resource
English
Intelligent transportation system , Traffic speed prediction , Gravitational search algorithm , Bi-LSTM network Engineering , Electrical Engineering , Automotive Engineering , Robotics and Automation , Computer Imaging, Vision, Pattern Recognition and Graphics , Civil Engineering , User Interfaces and Human Computer Interaction
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