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RESOLVING UNCERTAINTY WITHIN THE INDUCTIVE ENVIRONMENTAL MODEL IN GEOGRAPHIC INFORMATION SYSTEMS (GIS)

机译:在地理信息系统(GIS)的感应式环境模型中解决不确定性

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This paper discusses the application of Evidence Theory (plausibility reasoning) in a GIS for handling uncertainty-ambiguity associated with experts' inference in predicting the occurrence of active processes in particular areas. Based on how a model used in a GIS is constructed, the Inductive Environmental Model (IEM) is classified as a logical or inference processing model. By this is meant that this logical model is not based on a mathematical formula and does not admit to the application of error propagation theory. In this regard, the proposed IEM more closely represents the working of environmental expert than does the USLE mathematical model. Datasets on locational active processes (erosion class), influential related factors and their Certainty Factor (CF) obtained from the study area were used to provide an example of how the uncertainty-ambiguity associated with the IEM can be handled in a GIS environment.
机译:本文讨论了证据理论(合理性推理)在GIS中的应用,该模型用于处理与专家推断相关的不确定性-歧义,以预测特定区域中活动过程的发生。基于如何构造GIS中使用的模型,将归纳环境模型(IEM)归类为逻辑或推理处理模型。这意味着该逻辑模型不是基于数学公式,并且不接受错误传播理论的应用。在这方面,与USLE数学模型相比,拟议的IEM更能代表环境专家的工作。从研究区域获得的有关位置活动过程(侵蚀类),影响相关因子及其确定性因子(CF)的数据集提供了一个示例,说明了如何在GIS环境中处理与IEM相关的不确定性-歧义性。

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