Optimal Early Drought Detection Using Stochastic Process
Explore an optimal stopping approach for early drought detection, focusing on setting trigger levels based on precipitation measures. The goal is to determine the best time to send humanitarian aid by maximizing expected rewards and minimizing expected costs through suitable gain/risk functions. Tasks involve choosing a fitting stochastic process, designing appropriate functions, and setting penalties for false alarms and delays in trigger level detection.
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Presentation Transcript
Early drought detection: an optimal stopping approach
Trigger level Where should the trigger be set? Precipitation measures typically detect drought earlier because rainfall is a primary source. The usefulness of an early warning system is determined by the ratio of hits to false alarms.
Optimal stopping Goal: choose a time to take a particular action, in order to maximise an expected reward or minimise an expected cost. Consider a stochastic process and detect a stopping time at which some gain function is maximised or some risk function is minimised. In this case, find the optimal stopping time (trigger level) when to send humanitarian aids.
Tasks Choose a stochastic process which fits the data. Design a suitable gain/risk function: it may have the general form ?1? ????? ????? + ?2? ????????? ????? Set ?1to penalise false alarms (economical reasons) and ?2to penalise delays in the detection of the trigger level (humanitarian reasons).
