Quality metrics for assessing and forecasting critical condition
The problem of increasing the implementation reliability of complex systems eco- and biomonitoring process with the aim of anomalous and critical conditions timely detection and taking response measures to ensure a high human life quality is considered. Numerical metrics are proposed for the quality of mathematical models that analytically define the functional fields of the parameters studied, constructed from point measurements in the context of reducing the number of false positives when anomalies are detected. The tasks of optimizing the sample size and increasing the sensitivity to emerging anomalies in conditions of limited bandwidth of the mobile communication channel and speed are solved. An intelligent system has been proposed that, based on historical data from observation fields of the aquatic environment parameters, selects the optimal regression model and serves as the basis for the decision support system for choosing the optimal measurement intervals.