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A Knowledge Based Genetic Algorithm Approach to Automating Cartographic Generalisation

机译:一种基于知识的遗传算法来自动化制图泛化

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Rendering map data at scales smaller than their source can give rise to map displays exhibiting graphic conflict, such that objects are either too small to be seen or too close to each other to be distinguishable. Furthermore, scale reduction will often require important features to be exaggerated in size, sometimes leading to overlapping features. Cartographic Map generalisation is the process by which any graphic conflict that arises during scaling is resolved. In this paper, we show how a Genetic Algorithm approach was used to resolve spatial conflict between objects after scaling, achieving near optimal solutions within practical time constraints.
机译:在比其源小的尺度上渲染地图数据可以引起展示图形冲突的地图显示,使得物体太小而无法看到或彼此过于接近以可区分。此外,减少规模将往往需要大小夸大的重要特征,有时导致重叠的功能。制图映射概括是解决缩放期间出现的任何图形冲突的过程。在本文中,我们展示了如何使用遗传算法方法如何在缩放后解决物体之间的空间冲突,在实际限制中实现近最佳解决方案。

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