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In view of low reliability of leakage protection device of coal mine low-voltage power grid based on line selection principle of zero-sequence power direction, a hardware and software design scheme of mine-used low-voltage leakage protection device was given. Fault line selection is realized according to differences of phase difference between zero-sequence current and zero-sequence voltage in non-fault branch and fault branch when single-phase grounding fault occurs in zero-sequence reactor grounding system with parallel resistance. The simulation and test results show that the device is not affected by zero sequence reactor compensation in power grid, and can operate quickly and reliably when single-phase grounding fault occurs.

In this paper, we propose a multicategory large margin classification with unequal costs. In addition to extending the standard multicategory SVM to the case of unequal costs, we also develop an unequal costs classification for ψ-loss and propose an efficient algorithm for computation. Besides commonly used L2 penalty, the adaptive LASSO is also examined to remove irrelevant variables. Theoretically, we derive the Bayes rules under the generalized cost and reduce the infinite sum-to-zero constraint to a finite constraint. Numerically, we demonstrate the good performance of our methodology on two simulated examples and one real-life dataset. [ABSTRACT FROM AUTHOR]

In this article, we propose a semiparametric mixture of additive regression models, in which the regression functions are additive and non parametric while the mixing proportions and variances are constant. Compared with the mixture of linear regression models, the proposed methodology is more flexible in modeling the non linear relationship between the response and covariate. A two-step procedure based on the spline-backfitted kernel method is derived for computation. Moreover, we establish the asymptotic normality of the resultant estimators and examine their good performance through a numerical example. [ABSTRACT FROM PUBLISHER]

In this article, we propose the non parametric mixture of strictly monotone regression models. For implementation, a two-step procedure is derived. We further establish the asymptotic normality of the resultant estimator and demonstrate its good performance through numerical examples. [ABSTRACT FROM AUTHOR]