Jan 9, 2012 · This brief presents an innovative algorithm integrated with particle swarm optimization and artificial neural networks to develop short-term ...

In this paper, an effective framework, namely adaptive particle swarm optimization, APSO, is proposed based on simple multi-layer neural networks, in order to ...

Prediction of Short-term Traffic Variables using Intelligent Swarm-based Neural Networks ; Source Title. IEEE Transactions on Control Systems Technology ; DOI.

Oct 22, 2024 · This brief presents an innovative algorithm integrated with particle swarm optimization and artificial neural networks to develop short-term ...

A new framework has been proposed to improve the accuracy of traffic flow prediction. The proposed model is based on Bi-LSTM neural network with a modified PSO ...

Experimental findings demonstrated that the proposed PSO-Bi-LSTM model has significantly outperformed the other models in terms of accuracy and stability.

This paper presents an innovative algorithm integrated with particle swarm optimization and artificial neural networks to develop short-term traffic flow ...

The tested algorithm is found to provide accurate predictions with a computation time of less than one second without training. Furthermore, the algorithm shows ...

An approach to freeway travel time prediction based on recurrent neural networks is presented. Travel time prediction requires a modeling approach that is ...

This paper proposes a new hybrid model of grey system theory and neural networks with particle swarm optimization, namely,. GNN-PSO. The proposed hybrid model ...