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J Res Health Sci. 2023;23(3): e00592. doi: 10.34172/jrhs.2023.127
PMID: 38315907        PMCID: PMC10660506

Original Article

A Fuzzy Clustering Approach to Identify Pedestrians’ Traffic Behavior Patterns

Parisa Saeipour 1 ORCID, Parvin Sarbakhsh 1 * ORCID, Saman Salemi 2, Fatemeh Bakhtari Aghdam 3

Cited by CrossRef: 1

1- Pink M, Kiełbasa B, Niewiadomski M, Piecuch K. Barriers and Challenges Faced in the Deployment of Principles of the Circular Bioeconomy: Awareness, Knowledge and Practices Based on the Example of Polish Agriculture. Sustainability. 2025;17(10):4729 [Crossref]
2- Üzümcüoğlu Y, Yaşar M. Arada Kalmak: Yaya ve Sürücülerin Agresif Sürüşe Tepkilerinin İncelenmesi. 2025;8(1):15 [Crossref]
3- Liu J, Chen X. Analysis of pedestrian-two-wheeler conflicts at green light digital countdown signals: A random parameter ordered logit model approach. Accident Analysis & Prevention. 2024;206:107716 [Crossref]
4- Tavares E, Moita G, Silva A. eFC-Evolving Fuzzy Classifier with Incremental Clustering Algorithm Based on Samples Mean Value. BDCC. 2024;8(12):183 [Crossref]