Introducing an Evolving Local Neuro-Fuzzy Model – Application to modeling of car-following behavior
| Autor: | Reza Kazemi, Majid Abdollahzade |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
Engineering
Binary tree Neuro-fuzzy Process (engineering) business.industry Applied Mathematics Car following Computer Science Applications Traffic flow (computer networking) Nonlinear system Identification (information) Control and Systems Engineering Model application Artificial intelligence Electrical and Electronic Engineering business Instrumentation |
| Zdroj: | ISA Transactions. 59:375-384 |
| ISSN: | 0019-0578 |
| DOI: | 10.1016/j.isatra.2015.09.002 |
| Popis: | This paper proposes an Evolving Local Linear Neuro-Fuzzy Model for modeling and identification of nonlinear time-variant systems which change their nature and character over time. The proposed approach evolves through time to follow the structural changes in the time-variant dynamic systems. The evolution process is managed by a distance-based extended hierarchical binary tree algorithm, which decides whether the proposed evolving model should be adapted to the system variations or evolution is necessary. To represent an interesting but challenging example of the systems with changing dynamics, the proposed evolving model is applied to model car-following process in a traffic flow, as an online identification problem. Results of simulations demonstrate effectiveness of the proposed approach in modeling of the time-variant systems. |
| Databáze: | OpenAIRE |
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