文章基本信息

标题：Machine Learning Predictors for Sustainable Urban Planning
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作者：Sarojini Devi Nagappan ; Salwani Mohd Daud
期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2021
卷号：12
期号：7
DOI：10.14569/IJACSA.2021.0120787
语种：English
出版社：Science and Information Society (SAI)
摘要：While essential for economic reasons, rapid urbanization has had many negative impacts on the environment and the social wellbeing of humanity. Heavy traffic, unexpected geohazards are some of the effects of uncontrollable development. This situation points its fingerto urban planning and design; there are numerous automation tools to help urban planners assess and forecast, yet unplanned development still occurs, impeding sustainability. Automation tools use machine learning classification models to analyze spatial data and various trend views before planning a new urban development. Although there are many sophisticated tools and massive datasets, big cities with colossal migration still witness traffic jams, pollution, and environmental degradation affecting urban dwellers' quality. This study will analyze the current predictors in urban planning machine learning models and identify the suitable predictors to support sustainable urban planning. A correct set of predictors could improve the efficiency of the urban development classification models and help urban planners to enhance the quality of life in big cities.
关键词：Urban planning; sustainable development; urban development classification model; machine learning; urban development predictors