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Sustainable Industrial Site Redevelopment Planning Support: A Case-Based Reasoning Approach

机译:可持续工业用地再开发规划支持:基于案例的推理方法

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摘要

Abandoned industrial sites could be redeveloped in a sustainable way with the help of previous experience. This paper presents a case-based reasoning (CBR) approach to support sustainable industrial site redevelopment. For a target site that needs to be redeveloped, qualitative important key concerns are identified and quantitative attributes, which are important for sustainability, are calculated. The key concerns are generated from zoning documents and the attributes are calculated from spatial data sets. Machine learning techniques are used to find the most influential attributes to determine transition forms. Similar cases from the constructed case base are retrieved based on the algorithm the authors have proposed. The North Brabant region in the Netherlands is used as a case study. A web application is presented to illustrate the approach. The e-planning method provides a straightforward way to retrieve transition forms from similarly redeveloped cases for new regional planning tasks with a focus on sustainability.
机译:可以在以前的经验的帮助下以可持续的方式重新开发废弃的工业用地。本文提出了一种基于案例的推理(CBR)方法来支持可持续的工业用地再开发。对于需要重新开发的目标地点,要确定定性的重要重点并计算对可持续性至关重要的定量属性。关键问题是从分区文档中生成的,而属性是从空间数据集计算得出的。机器学习技术用于查找最有影响力的属性,以确定过渡形式。基于作者提出的算法,从构造的案例库中检索相似的案例。以荷兰的北布拉班特地区为例。提供了一个Web应用程序来说明该方法。电子计划方法提供了一种直接的方法,可以从针对新的区域规划任务的类似重建案例中检索过渡形式,重点是可持续性。

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