Economic Analysis of a Transport Company in the Aspect of Car Vehicle Operation
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- M Lezaun & G Pérez & E Sáinz de la Maza, 2006. "Crew rostering problem in a public transport company," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(10), pages 1173-1179, October.
- Helton, J.C. & Johnson, J.D. & Sallaberry, C.J. & Storlie, C.B., 2006. "Survey of sampling-based methods for uncertainty and sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 91(10), pages 1175-1209.
- Zhang, Guoqiang & Eddy Patuwo, B. & Y. Hu, Michael, 1998. "Forecasting with artificial neural networks:: The state of the art," International Journal of Forecasting, Elsevier, vol. 14(1), pages 35-62, March.
- Verhoef, Erik, 1994. "External effects and social costs of road transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 28(4), pages 273-287, July.
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Keywords
neural networks; transport of bulk materials; sensitivity analysis;All these keywords.
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