1. [1] Ferrero, A., Salicone, S. (2004). A Monte Carlo-like approach to uncertainty estimation in electric power quality measurement. COMPEL, 23 (1), 119-132. 10.1108/03321640410507590
2. [2] Jing, H., Huang, M.F., Zhong, Y.R., Kuang, B., Jiang, X.Q. (2007). Estimation of the measurement uncertainty based on Quasi Monte-Carlo Method in optical measurement. In International Symposium on Photoelectronic Detection and Imaging 2007: Optoelectronic System Design, Manufacturing, and Testing. SPIE 6624, 10 p.
3. [3] Joint Committee for Guides in Metrology. (2008). Evaluation of measurement data - Supplement 1 to the “Guide to the expression of uncertainty in measurement” - Propagation of distributions using a Monte Carlo method. JCGM 101:2008.
4. [4] Stryczek, R., Pytlak, B. (2014). Multi-objective optimization with adjusted PSO method on example of cutting process of hardened 18CrMo4 steel. Eksploatacja i Niezawodnosc - Maintenance and Reliability, 16 (2), 236-245.
5. [5] Stryczek, R., Dutka, P. (2016). The analysis of signal disruptions from the optical triangulation measurement sensor. Measurement Automation Monitoring, 62 (2), 62-65.