在地形对象的选择中使用粗略的规则来概括地理信息

A. Fiedukowicz
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引用次数: 1

摘要

摘要选择是制图概括过程的关键要素,通常是其第一阶段。另一方面,它是其他泛化运算符的组成部分,例如简化。泛化中使用的方法之一是条件-作用方法。作者采用了基于三种类型的粗糙逻辑(粗糙集理论(RST)、基于优势的粗糙集理论(DRST)和模糊粗糙集理论(FRST))的条件-作用方法,检验了它们在选择地形对象(建筑物、道路、河流)过程中使用的可能性,并比较了得到的结果。通过视觉评估,评估决策系统的复杂性(规则的数量及其条件)及其有效性,包括数量和质量。所进行的研究表明,DRST和RST方法(与CN2算法)的优势在于所获得的选择的质量,决策系统的更简单性,以及能够使用这些系统的更好的IT工具。在这个阶段,不建议采用以创建规则的最高复杂性和最差选择结果为特征的FRST方法。由于需要为其中使用的属性选择适当的度量尺度,特定的方法具有局限性。应特别注意网络对象的选择,其中仅使用条件-动作方法,而不保持网络的一致性,可能无法产生预期的结果。与基于经典逻辑的方法不同,粗糙方法允许使用不完整或矛盾的信息。所提出的工具可以(以其当前形式)在地形对象的选择中找到辅助用途,并且也可能在其他泛化算子中找到辅助用途。
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The use of rough rules in the selection of topographic objects for generalizing geographical information
Abstract Selection is a key element of the cartographic generalisation process, often being its first stage. On the other hand it is a component of other generalisation operators, such as simplification. One of the approaches used in generalization is the condition-action approach. The author uses a condition-action approach based on three types of rough logics (Rough Set Theory (RST), Dominance-Based Rough Set Theory (DRST) and Fuzzy-Rough Set Theory (FRST)), checking the possibility of their use in the process of selecting topographic objects (buildings, roads, rivers) and comparing the obtained results. The complexity of the decision system (the number of rules and their conditions) and its effectiveness are assessed, both in terms of quantity and quality – through visual assessment. The conducted research indicates the advantage of the DRST and RST approaches (with the CN2 algorithm) due to the quality of the obtained selection, the greater simplicity of the decision system, and better refined IT tools enabling the use of these systems. At this stage, the FRST approach, which is characterised by the highest complexity of created rules and the worst selection results, is not recommended. Particular approaches have limitations resulting from the need to select appropriate measurement scales for the attributes used in them. Special attention should be paid to the selection of network objects, in which the use of only a condition-action approach, without maintaining consistency of the network, may not produce the desired results. Unlike approaches based on classical logic, rough approaches allow the use of incomplete or contradictory information. The proposed tools can (in their current form) find an auxiliary use in the selection of topographic objects, and potentially also in other generalisation operators.
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