References
- Wei, Jo-Ting, et al. “Using feature selection in identifying critical fac- tors of injury severity.” Journal of Information and Optimization Scienc- es, 32.6 (2011): 1341-1352. doi: 10.1080/02522667.2011.10700123
- Mor, N., Sood, H. and Goyal, T, Development and Corroboration of crash prediction Model,International Journal of Pure and Applied Math- ematics, 119.15, pp.413-421, (2018).
- Chetna, Mor, N., Sood, H., Black Spots Identification on Pinjore to Baddi Road,International Journal of Pure and Applied Mathematics, 120.6, pp. 6473-6488, (2018).
- Mor, N. and Sood, H.,Correlation of Accident with Traffic Volume of NH-1,International Journal of Engineering Technology Science and Re- search, 4.7, pp.948-950, (2017).
- Dinu, R.R. and Veeraragavan, A., Random parameter models for ac- cident prediction on two-lane undivided highways in India,Journal of safety research, 42.1, pp.39-42, (2011). doi: 10.1016/j.jsr.2010.11.007
- Theofilatos, Athanasios, Daniel Graham, and George Yannis. “Fac- tors affecting accident severity inside and outside urban areas in Greece.” Traffic injury prevention 13.5 (2012): 458-467. doi: 10.1080/15389588.2012.661110
- Saxena, Punita, K. K. Dewan, and M. Mustafa. “Data envelopment analysis: an application in the transport sector.“ Journal of Interdisci- plinary Mathematics 9.2 (2006): 385-395. doi: 10.1080/09720502.2006.10700451
- Shafabakhsh, Gholam Ali, Afshin Famili, and Mahdi Akbari. “Spatial analysis of data frequency and severity of rural accidents.” Transpor- tation Letters (2016): 1-8.