Excellent approach to modeling urban expansion by fuzzy cellular automata: agent base model

2014 ◽  
Author(s):  
Yousef Khajavigodellou ◽  
Ali A. Alesheikh ◽  
Abdulrazak A. S. Mohammed ◽  
Kamran Chapi
Keyword(s):  
Cellular Automata ◽  
Urban Expansion ◽  
Fuzzy Cellular Automata ◽  
Agent Base Model

Accelerating fuzzy cellular automata for modeling crowd dynamics

2019 ◽  
Vol 32 ◽  
pp. 125-140 ◽  
Author(s):  
Ioannis Gerakakis ◽  
Prodromos Gavriilidis ◽  
Nikolaos I. Dourvas ◽  
Ioakeim G. Georgoudas ◽  
Giuseppe A. Trunfio ◽  
...  
Keyword(s):  
Cellular Automata ◽  
Crowd Dynamics ◽  
Fuzzy Cellular Automata

Modelling urban sprawl using fuzzy cellular automata model for the city of Jaipur

2018 ◽  
Vol 10 (4) ◽  
pp. 285
Author(s):  
Pushpendra Singh Sisodia ◽  
Rajveer Singh Shekhawat ◽  
Vivekanand Tiwari
Keyword(s):  
Cellular Automata ◽  
Urban Sprawl ◽  
Cellular Automata Model ◽  
Fuzzy Cellular Automata ◽  
The City

scholarly journals Modeling of Urban Growth Using Cellular Automata and GIS Case of Benslimane in Morocco

2020 ◽  
Author(s):  
BENCHELHA MOHAMED ◽  
Benzha Fatiha ◽  
Rhinane Hassan ◽  
BENCHELHA SAID ◽  
BENCHELHA TAOUFIK ◽  
...  
Keyword(s):  
Land Use ◽  
Cellular Automata ◽  
Urban Growth ◽  
Urban Expansion ◽  
Confusion Matrix ◽  
Spatial Transformation ◽  
Urban Growth Modeling ◽  
Main Component Analysis ◽  
Spatio Temporal ◽  
Main Component

In this study, our goal was to research land-use change by combining spatio–temporal land use/land cover monitoring (LULC (1989–2019) and urban growth modeling (1999–2039) in Benslimane, Morocco, to determine the effect of urban growth on different groups based on cellular automata (CA) and geospatial methods. A further goal was to test the reliability of the AC algorithm for urban expansion modeling. To do this, four years of satellite data were used at the same time as population density, downtown distance, slope, and ground road distance. The LULC satellite reported a rise of 3.8 km2 (318% variation) during 1989–2019. Spatial transformation analysis reveals a good classification similarity ranging from 89% to 91% with the main component analysis (PCA) technique. The statistical accuracy between the satellite scale and the replicated built region of 2019 gave 97.23 %t of the confusion matrix overall accuracy, and the region under the receiver operational characteristics (ROC) curve to 0.94, suggesting the model's high accuracy. Although the constructed area remains low relative to the total area of the municipality's territory, the LULC project shows that the urban area will extend to 5,044 km2 in 2019, principally in the western and southwestern sections. In 2019–2039, urban development is expected to lead to a transformation of the other class (loss of 1,364 km2), followed by vegetation cover (loss of 0.345 km2). In spatial modeling and statistical calculations, the GDAL and NumPy Python 3.8 libraries were successful.

Simulation of urban expansion based on cellular automata and maximum entropy model

2020 ◽  
Vol 63 (5) ◽  
pp. 701-712 ◽  
Author(s):  
Yihan Zhang ◽  
Xiaoping Liu ◽  
Guangliang Chen ◽  
Guohua Hu
Keyword(s):  
Cellular Automata ◽  
Maximum Entropy ◽  
Urban Expansion ◽  
Maximum Entropy Model ◽  
Entropy Model

An Improved Method for Edge Detection and Image Segmentation Using Fuzzy Cellular Automata

2016 ◽  
Vol 47 (3) ◽  
pp. 161-179 ◽  
Author(s):  
Reza Shahverdi ◽  
Madjid Tavana ◽  
Ali Ebrahimnejad ◽  
Khadijeh Zahedi ◽  
Hesam Omranpour
Keyword(s):  
Image Segmentation ◽  
Cellular Automata ◽  
Edge Detection ◽  
Improved Method ◽  
Fuzzy Cellular Automata

Incorporation of spatial anisotropy in urban expansion modelling with cellular automata

2020 ◽  
pp. 1-28
Author(s):  
Jinqu Zhang ◽  
Yu Ling ◽  
A-Xing Zhu ◽  
Hongyun Zeng ◽  
Jia Song ◽  
...  
Keyword(s):  
Cellular Automata ◽  
Urban Expansion ◽  
Spatial Anisotropy

Substation Remote Viewing Image Mosaic Based on Fuzzy Cellular Automata Detection

2013 ◽  
Vol 846-847 ◽  
pp. 1213-1216
Author(s):  
Hong Tao Zai
Keyword(s):  
Cellular Automata ◽  
Feature Point ◽  
Image Mosaic ◽  
Feature Points ◽  
System A ◽  
Safety And Reliability ◽  
Fuzzy Cellular Automata ◽  
Remote Viewing ◽  
Matched Edge ◽  
Edge Feature

In order to improve the effect of remote video monitoring system, a new image mosaic technology based on fuzzy cellular automata detection is presented. Firstly, the edge feature points from two images are extracted by fuzzy cellular automata; secondly, the corresponding feature point pairs are got by the cross-correlation of the gray scale around the edge feature points; finally the images can be stitched by matched edge feature point pairs. The experiment of remote viewing image mosaic in substation shows that this method can achieve image mosaic effectively and it will be benefit to improve the safety and reliability of substation operation.

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