Automatic freeway incident detection system and method using artificial neural network and genetic algorithms
US6470261B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 16, 2001 |
| Grant date | Oct 22, 2002 |
| Priority date | — |
| Expiry date | Jan 16, 2021 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V10/82
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Design of a neural network for automatic detection of incidents on a freeway is described. A neural network is trained using a combination of both back-propagation and genetic algorithm-based methods for optimizing the design of the neural network. The back-propagation and genetic algorithm work together in a collaborative manner in the neural network design. The training starts with incremental learning based on the instantaneous error and the global total error is accumulated for batch updating at the end of the training data being presented to the neural network. The genetic algorithm directly evaluates the performance of multiple sets of neural networks in parallel and then use the analyzed results to breed new neural networks that tend to be better suited to the problems at hand.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.