Urban growth modeling based on cellular automata with transition rules optimized using genetic fuzzy systems-Reference-Cited by-同舟云学术

Urban growth modeling based on cellular automata with transition rules optimized using genetic fuzzy systems

Published:2022-11 Issue:8 Volume:26 Page:3253-3276
ISSN:1361-1682
Container-title:Transactions in GIS
language:en
Short-container-title:Transactions in GIS

Author:

Foroutan Ehsan¹^ORCID,Delavar Mahmoud Reza²^ORCID,Pijanowski Bryan Christopher³^ORCID,Araabi Babak Nadjar⁴^ORCID

Affiliation:

1. Department of Geography Oklahoma State University Stillwater Oklahoma USA

2. Center of Excellence in Geomatic Eng. in Disaster Management, School of Surveying and Geospatial Eng., College of Engineering, University of Tehran Tehran Iran

3. Department of Forestry and Natural Resource, College of Agriculture Purdue University West Lafayette Indiana USA

4. School of Electrical and Computer Engineering, College of Engineering University of Tehran Tehran Iran

Publisher

Wiley

Subject

General Earth and Planetary Sciences

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/tgis.13000

Reference55 articles.

1. Improving the capability of an integrated CA-Markov model to simulate spatio-temporal urban growth trends using an Analytical Hierarchy Process and Frequency Ratio

2. Calibration of a fuzzy cellular automata model of urban dynamics in Saudi Arabia

3. A MULTI-OBJECTIVE GENETIC ALGORITHM FOR TUNING AND RULE SELECTION TO OBTAIN ACCURATE AND COMPACT LINGUISTIC FUZZY RULE-BASED SYSTEMS

4. Fuzzy inference guided cellular automata urban‐growth modelling using multi‐temporal satellite images

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