Analysis of Crowd Flow Parameters Using Artificial Neural Network
| Autor: | K.V.R. Ravishankar, Poojari Yugendar |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Artificial neural network
Computer science business.industry 020208 electrical & electronic engineering General Engineering 020206 networking & telecommunications 02 engineering and technology deterministic models macroscopic flow diagram mae K4011-4343 Transportation and communication Computer Science Applications rmse Flow (mathematics) 0202 electrical engineering electronic engineering information engineering greenshield Artificial intelligence business ann |
| Zdroj: | Transport and Telecommunication, Vol 19, Iss 4, Pp 335-345 (2018) |
| ISSN: | 1407-6179 |
| Popis: | Research scientists have been developing mathematical tools to detect objects, recognize objects and actions, and discover behaviours and events to human abilities. In all these efforts, the understanding of human actions is of a special interest for both application and research purposes. In this study, crowd flow parameters are analysed by considering linear and non linear relationships between stream flow parameters using conventional and soft computing approach. Deterministics models like Greenshield and Underwood were applied in the study to describe flow characteristics. A non-linear model based on Artificial Neural Network (ANN) approach is also used to build a relationship between different crowd flow parameters and compared with the other deterministic models. ANN model gave good results based on accuracy measurement to deterministic models because of their self-processing and intelligent behaviour. Mean absolute error (MAE) and root mean square error (RMSE) values for the best fitted ANN model are less than those for the other models. ANN model gives better performance in fitness of model and future prediction of flow parameters. |
| Databáze: | OpenAIRE |
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