This paper presents the inference algorithm for a qualitative modeling program called QTIP (Qualitative Temporal inference Program). This program was developed for use in crop management decision support systems. The algorithm presented here is used to diagnose possible disorders leading to abnormal values in data collected as a part of the crop management process. QTIP employs rules representing cause and effect relationships to generate qualitative dynamic scenarios. Its diagnostic algorithm is a hypothetical reasoning scheme consisting of alternating applications of abduction, to identify possible causes of observed conditions, and deduction, to maintain internal consistency. The algorithm is illustrated through application to a simple model for a hypothetical small grain crop.
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