Open AccessGenerating Residential Layout Based on AI in the View of Wind Environment
Author(s) -
Xiaoyu Ying,
Xiaoying Qin,
J H Chen,
Jing Shu Gao
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2069/1/012061
Subject(s) - scheduling (production processes) , computer science , plan (archaeology) , function (biology) , plot (graphics) , page layout , industrial engineering , architectural engineering , engineering , operations management , statistics , mathematics , archaeology , evolutionary biology , biology , advertising , business , history
There is a contradiction between the high-density residential area development form and comfortable outdoor physical environment. The existing studies on wind environment of high-rise residential areas only provide the guidance for the simple general layouts, which cannot cope with the fact that most high-rise residential areas are mixed of point buildings and board buildings, and it would cost a lot of time and resources to carry out computer simulation of each layout. This paper presents a new tool, which uses the automatic optimization function of genetic algorithm and the prediction function of fully convolutional neural network to integrates three functions: the automatic generation of high-rise residential layout, the simulation of wind environment and the comparison for optimization, to learn plan scheduling and obtain the optimal solution for high-rise residential layout under specific plot ratio and plot conditions, provides guidance for today’s fast-paced architectural design.