| Summary: | 博士 === 淡江大學 === 資訊工程學系 === 91 === This dissertation proposes a method that contains the knowledge of experts in the Inference system while developing expert system. However, the process of establishing are so complicated, redundant, and professional such that the expert system can’t be applied into all levels. Furthermore, expert system must build on stationary input information and stable inferred individual. But, the unsure of the inferring individual, continuously entering or exiting by the new inferring individuals during system built or inferred time cause the inferred individual dynamic change, and then affect the establishing of the system.On the other hand, all the required information of environmental factor may get from historical data. The information of environmental factor can be sufficiently understood because the collected information is environment historical data while the system is building. However, during the time of system building, although the historical data may be complete, the information of environmental factor may not be gained during inferring because of the publish time. During the inferring process, theoretically the information of environmental factor should be very clear. In fact, we may not completely collect the data. The information of environmental factor may not be collected immediately because they are either used for data statistics or still incomplete.This paper proposes a Dynamic Decision Support System Model, which is an expert-based decision support system model that establishes initial model, automatically complement the incomplete information and satisfy the dynamic decision information during inferring, and provides decision and help with the minimum information to build a perfect decision system model.
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