Abstract

By establishing a database of urban space cases, machine learning algorithms and deep learning algorithms can be used to train computers to learn how to design urban spaces. Based on the basic concepts of machine learning and deep learning and their procedural logic, this paper explores the generation mode of traffic road network, neighborhood space form, and building function layout of urban space and uses the northern extension of the central green axis of the city as an application case to confirm its feasibility in order to seek a set of artificial intelligence-based urban space generation design method and provide a new idea for the innovative development of urban design methods.

Highlights

  • Urban physical space is a multilayered, open, and complex system. e factors that need to be considered for a good urban space design are numerous and interacting and change from place to place and from time to time [1, 2]

  • Space of most cities lacks recognition and attractiveness, resulting in a dull image of the city and a lack of “connotation” [3, 4]. e following reasons have given rise to the phenomenon of “one city for all” to a certain extent: urban design elements have become more diversified, and more and more branches have been derived in terms of spatial topology, functional scope, and cultural connotation, and the information content that urban design needs to digest and cover has become more complicated

  • Designers are constantly searching for designs that break through dilemmas and are personalized through an iterative approach to urban space design

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Summary

Introduction

Urban physical space is a multilayered, open, and complex system. e factors that need to be considered for a good urban space design are numerous and interacting and change from place to place and from time to time [1, 2]. E research on the combination of urban public space and artificial intelligence is still at the level of traditional vision, using a variety of machine learning methods to measure and count various visual elements such as greenery and buildings on a large-scale and supporting traditional geographic means for evaluation. E five elements of urban design are boundaries, roads, districts, nodes, and landmarks Based on these five elements, the database of urban space cases is set into three subdatabases: urban traffic network information database, urban neighborhood spatial form database, and urban building functional layout database.

Determination of final urban design scheme
Evaluation and calculation of BP neural network
Python crawler
Illumination Intensity
Full Text
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