Predictive models for voltage reference elements monitoring

In this paper we use predictive models for monitoring the behavior of voltage reference elements (VRE-s). The predictive abilities of different paradigms, such as neural network-based predictors, support vector machine (SVM) for regression and difference equation predictors are compared. The predictive models are used to estimate the next voltage values without performing measurements. The models for short-term prediction are previously trained by using long-term measurements of voltage, preformed by high-precision digital voltmeter. Due to the robustness of the predictors, the voltage estimation is allowed without performing measurements. Thus, we obtain transparent and adaptive measurement system.