Improving Genetic Algorithms for Optimal Land-Use Allocation-Reference-Cited by-同舟云学术

Improving Genetic Algorithms for Optimal Land-Use Allocation

Published:2021-12 Issue:4 Volume:147 Page:04021049
ISSN:0733-9488
Container-title:Journal of Urban Planning and Development
language:en
Short-container-title:J. Urban Plann. Dev.

Author:

Gharaibeh Anne A.¹^ORCID,Ali Mansoor H.²,Abo-Hammour Zaer S.³,Al Saaideh Mohammad⁴

Affiliation:

1. Associate Professor, Dept. of City Planning and Design, Jordan Univ. of Science and Technology, Irbid 22110, Jordan (corresponding author). ORCID: .

2. Planner, MUP, Dept. of City Planning and Design, Jordan Univ. of Science and Technology, Irbid 22110, Jordan.

3. Professor, Dept. of Mechatronics Engineering, Univ. of Jordan, Amman 11942, Jordan.

4. Research Assistant, Dept. of Electrical Engineering, Univ. of Jordan, Amman 11942, Jordan.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Urban Studies,Development,Geography, Planning and Development,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29UP.1943-5444.0000744

Reference57 articles.

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2. Using Linear Integer Programming for Multi-Site Land-Use Allocation

3. Åkerlund, U. 2011. Stockholm’s green wedges–concepts, learning and collaboration on urban and peri-urban forestry. Stockholm, Sweden: Swedish National Board of Housing, Building and Planning.

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

5. Using neural networks and cellular automata for modelling intra‐urban land‐use dynamics

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