Time Delay Neural Networks Designed Using Genetic Algorithms for Short Term Inter-City Traffic Forecasting

Authors:
Pawan Lingras;Paul Mountford
Affiliations:
-;-
Venue:
Proceedings of the 14th International conference on Industrial and engineering applications of artificial intelligence and expert systems: engineering of intelligent systems
Year:
2001

Citing 5
Cited 2

Neurocomputing

Neurocomputing
Adaptation in natural and artificial systems

Adaptation in natural and artificial systems
Designing Neural Networks using Genetic Algorithms

Proceedings of the 3rd International Conference on Genetic Algorithms
Towards the Genetic Synthesisof Neural Networks

Proceedings of the 3rd International Conference on Genetic Algorithms
Training feedforward neural networks using genetic algorithms

IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1

Letters: Computational intelligence-based congestion prediction for a dynamic urban street network

Neurocomputing
Dynamic neural networks applied to melody retrieval

MICAI'10 Proceedings of the 9th Mexican international conference on Artificial intelligence conference on Advances in soft computing: Part II

Quantified Score

Hi-index	0.00

Visualization

Abstract

Estimation of short-term traffic volumes is an important issue in the development of intelligent transportation systems (ITS). This paper uses genetic algorithms to maximize statistical correlation for selecting connections between input and hidden layers of a time delay neural network for inter-city traffic volume estimations. The predictions for high traffic volume hours using proposed approach reflect a high degree of accuracy.