Effect of Ignoring Input Correlation on Truck-Shovel Simulation
作者： Sisi Que , Angelina Anani , Kwame Awuah-Offei
DOI: 10.1080/17480930.2015.1099188
关键词: Correlation function 、 Discrete event simulation 、 Distance correlation 、 Covariance and correlation 、 Sum of normally distributed random variables 、 Statistics 、 Multivariate t-distribution 、 Probability distribution 、 Computer science 、 Partial correlation
摘要: AbstractThis paper presents an approach for handling correlated input variables in discrete event simulation (DES) modelling of truck–shovel systems using commercial DES software and uses a case study to investigate the effect ignoring correlation between variables. Multivariate random vectors, instead independent probability distributions, are used found be correlated. The authors prove that correlations do exist haulage systems. model with multivariate vectors performs better than original model. significance depends on strength output’s sensitivity
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