Dadan Nugraha, I. Lesmana, Gian Megantara
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引用次数: 0

摘要

空间规划是每个区域政府必须履行的义务。目前,空间规划仍是传统的由空间规划公司进行规划。对于笔者考察的研究对象,即汉塔拉村,汉塔拉村对于汉塔拉村未来如何规划和发展还没有一个规划。随着信息技术的发展,目前空间规划可以通过将遗传算法实施到应用程序中来使用应用程序来完成。遗传算法是一种优化搜索算法,在其实施过程中,遗传算法将寻找最优点,这些点与2007年关于空间规划的第26号法律确定的约束相匹配。然后利用在线地图提供商mapbox的特性将遗传算法数据的搜索结果可视化。在软件开发中,作者使用Rational统一过程(RUP)方法,它有四个阶段,即:先启、精化、构建和产品化。此应用程序是使用python编程语言构建的,以及用于可视化数据的html和javascript。根据本文的研究结果,作者可以得出结论:本研究可以根据遗传算法及其约束对汉塔拉村的居住面积进行投影。关键词:空间规划,遗传算法,数据可视化,RUP, Python
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Implementasi Algoritma Genetika pada Tata Ruang Ibukota Kecamatan (Studi Kasus : Desa Hantara)
Spatial planning is an obligation that must be carried out by each Regional Government. At present, spatial planning is still conventionally planned by the spatial planning company. Regarding with the object of research that the authors examined, namely Hantara Village, Hantara Village did not yet have a plan for how the future projection and development of Hantara Village. With a touch of information technology, for now spatial planning can be done using an application by implementing a method that is Genetic Algorithm into the application .Genetic Algorithm is an optimal search algorithm which is in its implementation the genetic algorithm will look for the most optimal points which is match with the constraints that have been determined based on law 26 of 2007 concerning Spatial Planning. Then the search results of the genetic algorithm data will be visualized by using the features of the mapbox, the online map provider. In software development, the author use the Rational Unified Process (RUP) method which has four stages, namely: Inception, Elaboration, Contruction, and Transition. This application is built use the python programming language, along with html and javascript for visualizing the data. Based on the results of this research the authors can conclude that this research can make a projection of residental area in Hantara village accordance with genetic algorithm and its constraint.Keywords— Sepatial Planning, Genetic Algorithm, Data Visualization, RUP, Python
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