Abstract
This paper presents configuration design knowledge to solve irrigation scheduling problem in agriculture domain and a general approach for configuration management knowledge. It also introduces a Configuration Agriculture Irrigation Schedule (CAIS) tool that produces the configuration irrigation schedule design according to the CommonKADS methodology. A configuration that satisfy the user requirements, and that additionally satisfy some optimality criteria is required. By integrating Dynamic programming and inference knowledge, with demand including different objective, that it is used in generating the inference steps (PPSM) to select the suitable components of the inference steps minimizing the number of components and/or maximizing the accuracy of the result of each inference step. Operations Research techniques greatly improved the understanding of the interactions of a large number of components and enhanced the decision selection under uncertain outcomes.
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