The Cost Monitoring of the Construction Machinery with Using the Stochastic Progress-Based S-curves

[1] Tažiková, A. and Kozlovská, M. (2013). Approach to estimated construction time for project management. In: ITCRES 2013: Innovative trends in construction and real estate sector. Bratislava: STU, p. 1-11. - ISBN 978-80-227-3932-0.Search in Google Scholar

[2] Kozlovská, Mária (2013). Key factors of the managing of the construction projects (In Slovak: Kľúčové riziká riadenia stavebných projektov). In: Oceňovanie a riadenie stavebných projektov. Košice : TU, p. 62-69. - ISBN 978-80-553-1417-4.Search in Google Scholar

[3] Mesároš, F. and Mesároš, P. (2009). Controlling nákladov na stavebné procesy. Košice: VÚSI. 220 p.Search in Google Scholar

[4] Zou, P.X.W., Zhang, G., Wang, J.(2007). Understanding the key risks in construction projects in China. International Journal of Project Management (25), p. 601-614.10.1016/j.ijproman.2007.03.001Search in Google Scholar

[5] Barraza, Gabriel A., Back, W. Edward, Mata, Fernando (2004). Probalistic forecasting of project performance using stochastic S curves. Journal of Construction Engineering and Management. 130 (1), p. 25-32.10.1061/(ASCE)0733-9364(2004)130:1(25)Search in Google Scholar

[6] Crandall, K. C., and Woolery, J. C. (1982). Schedule development under stochastic scheduling. J. Constr. Div., Am. Soc. Civ. Eng., 108(2), 321-329.10.1061/JCCEAZ.0001044Search in Google Scholar

[7] Marshall, Robert. The Contribution of Earned Value Management to Project Success of Contracted Efforts. Journal of Contract Management, 2007, pp. 21-331.Search in Google Scholar

[8] A Guide to the Project Management Body of Knowledge. Newtown Square, PA: Project Management Institute. 2013. pp. 217-219.Search in Google Scholar

[9] Cheng, T., Venugopal, M., Teizer, J., Vela, P., A.(2011). Performance evaluation of ultra wideband technology for construction resource location tracking in harsh environments. Automation in Construction. 20 (8), 1173-1184. DOI: 10.1016/j.autcon.2011.05.001.10.1016/j.autcon.2011.05.001Search in Google Scholar

[10] Han, S., Lee, S., Hong, T., Chang, H. (2006). Simulation analysis of productivity variation by global positioning system (GPS) implementation in earthmoving operations. Canadian Journal of Civil Engineering . 33 (2), 1105-1114.10.1139/l05-124Search in Google Scholar

[11] Mesaroš, F. (2009). Oceňovanie stavebných prác z hľadiska času a presnosti. In: Realizácia a ekonomika stavieb, Košice : Dom techniky, p.150- 156 - ISBN 978-80-232-0301-1.Search in Google Scholar

[12] Barraza, Gabriel A., Back, W. Edward, Mata, Fernando (2006). Probalistic monitoring of project performance using SS curves. In: Journal of Construction Engineering and Management. 126 (2) p. 142-148.10.1061/(ASCE)0733-9364(2000)126:2(142)Search in Google Scholar

[13] Radziszewska-Zielina, E., Sobotka, A., Plebankiewicz, E., Zima, K (2013). Preliminary identification and evaluation of parameters affecting the capacity of the operator-earthmoving machine system, Budownictwo i architektura, 12 (2), pp. 53-60.10.35784/bud-arch.2173Search in Google Scholar

[14] Struková, Z., Ištvánik, M. (2011) Tools for mobile crane selecting and locating, International Review of Applied Sciences and Engineering, 2, pp. 69-74.10.1556/irase.2.2011.1.11Search in Google Scholar

[15] Assakkaf, I. ENCE 420 - Construction Equipment and Methods [online]. http://www.assakkaf.comCoursesENCE420Lectureschapter3c.pdfSearch in Google Scholar

[16] Gašparík, J. et al. (2013). Multi-criteria optimizing method of earthwork machine group selection implemented into soil processes, ISARC 2013 - 30th International Symposium on Automation and Robotics in Construction and Mining, Montreal, , pp. 448-458.10.22260/ISARC2013/0048Search in Google Scholar

[17] Milajić, A. et al. (2011). Genetic algorithms for assigning tasks to construction machine operators, Gradevinar, 63(8), pp. 749-755. Search in Google Scholar