YI Jun, LI Taifu, ZHANG Yuantao, et al. Multi-parameter correlation analysis based on mixed Copula model for aluminum reduction cell[J]. CIESC Journal, 2014, (4): 1327-1332.
YI Jun, LI Taifu, ZHANG Yuantao, et al. Multi-parameter correlation analysis based on mixed Copula model for aluminum reduction cell[J]. CIESC Journal, 2014, (4): 1327-1332.DOI: 10.3969/j.issn.0438-1157.2014.04.024.
It is difficult to accurately describe probability distribution and to do correlation analysis of operating multiple parameters in aluminum reduction cells. A correlation analysis method based on mixed Copula model was proposed to resolve the problem. First of all
non-parametric kernel density estimation method was used to establish edge density function of variables in the case of unknown distribution type. Secondly
proportion of contribution of different Copula functions could be adjusted by weight parameters in the joint distribution function of multiple parameters. Finally
the maximum likelihood method was used to estimate the mixed model parameters. By using 1824 groups real data of 170 kA operating aluminum smelter from a factory
test results showed that this method was better than other single Copula function because three distance indicators were 0.3169
0.6239 and 0.9276. It was an effective way under super-low-voltage condition to do multi-parameter correlation analysis with non-steady-state and non-uniform features.