Application of Genetic Algorithm to Spatial Distribution in Urban Planning

2008 ◽  
Author(s):  
Hu Xin ◽  
Zhang Zhi-xia
Keyword(s):  
Genetic Algorithm ◽  
Spatial Distribution ◽  
Urban Planning

scholarly journals Rationality analysis of urban spatial distribution and development direction based on environmental impact assessment——On to the Jianghua Yao nationality autonomous county

2020 ◽  
Vol 143 ◽  
pp. 01006
Author(s):  
Zhe Li ◽  
Yidan Wang ◽  
Shuyuan Tong
Keyword(s):  
Spatial Distribution ◽  
Urban Planning ◽  
Environmental Impact ◽  
Natural Resources ◽  
Impact Assessment ◽  
Environmental Impact Assessment ◽  
Negative Impact ◽  
Space Structure ◽  
Assessment Index ◽  
Development Direction

The rational planning of urban spatial distribution and development direction could benefit the urban economy, social environment and other aspects, as an essential part of urban planning. Since the Law of EIA promulgated in 2003, the scope of environmental impact assessment has been upgraded to a higher level of overall urban planning whereas the influence is not significant. In 2018, urban and rural planning function was merged into the Ministry of Natural Resources, from leading urban construction to serving the protection of urban natural resources. It is also a new and significant approach to analyse the rationality of urban spatial distribution and development direction from the perspective of environmental impact assessment. The purpose of Jianghua Yao autonomous county is to build an eco-tourism civilized city, which is representative in the selection of cities for environmental impact assessment. On the space structure of functional areas and the development direction to the indicator elements of Yao nationality autonomous county class was divided into 4 categories, 5 layers,15 index factors were selected to construct the environmental impact assessment index system. Using analytic hierarchy process (AHP) to select the indexes weights assignment, then according to the evaluation criterion to evaluate it, we draws the analysis conclusion in the environment aspect. The planned urban spatial distribution and development direction of Jianghua Yao autonomous county from 2014 to 2020 are reasonable, have little negative impact on the environment, and are suitable for the green development of the city.

AN ADAPTIVE BOOLEAN AUTOMATON TO MODEL CIRCADIAN CYCLES

1996 ◽  
Vol 07 (01) ◽  
pp. 83-99
Author(s):  
R.P.J. PERAZZO ◽  
A. SCHUSCHNY
Keyword(s):  
Genetic Algorithm ◽  
Spatial Distribution ◽  
Cellular Automaton ◽  
Evolutionary Process ◽  
Living Organism ◽  
Motor Output ◽  
Connectivity Pattern ◽  
Vital Functions ◽  
Free Running ◽  
Boolean Gates

We propose a Boolean cellular automaton to model an artificial adaptive living organism in order to investigate the development of cyclic vital functions during a simulated evolutionary process. The organism is endowed with a basic architecture consisting of several sensor (input), motor (output) and processing Boolean gates whose connectivity pattern is adapted with a genetic algorithm. Cyclic searching behaviors develop that are tuned to the spatial distribution of “food”. Under additional assumptions we also find that internal pacemakers can develop to adapt plastically to the alternance of “light” and “darkness”. These pacemakers coexist with a “free running” regime in which the circadian cycles persist even in the absence of external periodic stimuli.

scholarly journals Multiobjective Optimization Model of Residential Spatial Distribution

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Xia Li ◽  
Chengxiang Zhuge ◽  
Xiang Zhang ◽  
Jian Gao ◽  
Hui Zhang
Keyword(s):  
Genetic Algorithm ◽  
Spatial Distribution ◽  
Multiobjective Optimization ◽  
Optimization Model ◽  
Traffic Congestion ◽  
Social Benefit ◽  
Satisfactory Solution ◽  
Multiobjective Genetic Algorithm ◽  
Total Travel Time ◽  
Aggregate Utility

The concept of jobs-housing balance has been adopted as an effective way to alleviate the traffic congestion, especially in metropolis. A multiobjective model of residential spatial distribution (MOOMRSD) is developed in this paper to address the problem of how to locate the housing in a reasonable way when the workplace location is given. Three objectives are integrated into the MOOMRSD and they are (1) minimizing the average commute cost from residence to workplace; (2) minimizing the total travel time of citizens; and (3) maximizing the aggregate utility and social benefit. In addition, a multiobjective genetic algorithm (MOGA) is proposed to figure out a satisfactory solution to the MOOMRSD. Finally, Both MOOMRSD and MOGA are applied into two cases.

scholarly journals A Study of Spatiotemporal Distribution of Mobility-On-Demand in Generating Pick-Up/Drop-Offs Location Placement

Smart Cities ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 746-766
Author(s):  
Ryan K. Gunawan ◽  
Susilawati Susilawati
Keyword(s):  
Genetic Algorithm ◽  
Spatial Distribution ◽  
Spatiotemporal Distribution ◽  
Walking Distance ◽  
Clustering Method ◽  
Location Optimization ◽  
Demand Distribution ◽  
On Demand ◽  
Time Periods ◽  
The Difference

The location placement of pick-up/drop-offs of ride hailing usually only considers spatial distribution within a certain area. Previous studies often mapped out the potential hotspots for pick-up/drop-offs, benefitting the ride-hailing company and not considering the passengers. Therefore, in this study, we incorporated the spatiotemporal distribution of mobility-on-demand on generating pick-up/drop-off location placement using a genetic algorithm considering the walking distance and minimum demand data served within the radius. The data collected are analyzed through the clustering method, and the resulting cluster centers are fed into the location optimization algorithm. The genetic algorithm is used to optimize the location placement with the consideration of the user’s walking distance and demand. The algorithm is able to find an appropriate placement and determine reliable pick-up/drop-off stations within the study area based on observed spatiotemporal demand despite the difference in demand distribution through different time periods.

scholarly journals Quantifying the Urban Visual Perception of Chinese Traditional-Style Building with Street View Images

2020 ◽  
Vol 10 (17) ◽  
pp. 5963
Author(s):  
Liying Zhang ◽  
Tao Pei ◽  
Xi Wang ◽  
Mingbo Wu ◽  
Ci Song ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Deep Learning ◽  
Visual Perception ◽  
Urban Planning ◽  
Quantitative Research ◽  
Quantitative Method ◽  
Chinese Culture ◽  
Data Sources ◽  
Psychological States ◽  
Deep Learning Model

As a symbol of Chinese culture, Chinese traditional-style architecture defines the unique characteristics of Chinese cities. The visual qualities and spatial distribution of architecture represent the image of a city, which affects the psychological states of the residents and can induce positive or negative social outcomes. Hence, it is important to study the visual perception of Chinese traditional-style buildings in China. Previous works have been restricted by the lack of data sources and techniques, which were not quantitative and comprehensive. In this paper, we proposed a deep learning model for automatically predicting the presence of Chinese traditional-style buildings and developed two view indicators to quantify the pedestrians’ visual perceptions of buildings. Using this model, Chinese traditional-style buildings were automatically segmented in streetscape images within the Fifth Ring Road of Beijing and then the perception of Chinese traditional-style buildings was quantified with two view indictors. This model can also help to automatically predict the perception of Chinese traditional-style buildings for new urban regions in China, and more importantly, the two view indicators provide a new quantitative method for measuring the urban visual perception in street level, which is of great significance for the quantitative research of tourism route and urban planning.

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