Optimize Decision Model for Urban Land Development Using Disc Fermatean Fuzzy Information With Z-Numbers

Urban land development choices manifest complex, ambiguous situations where multiple criteria are involved, making it hard for traditional evaluation methods to address them effectively. The present study introduces an advanced methodological view called the Disc Fermatean Fuzzy Z-Number (D-FFZN) method developed to enhance the accuracy and reliability of urban planning decisions by skillfully addressing uncertainties. The D-FFZN approach was applied in the selection of optimal land development alternatives in a case study through newly formulated aggregation operators based on the weighted averaging and weighted geometric methods. To confirm the method’s performance, a comparative analysis was undertaken between the D-FFZN method and a more renowned multi-criteria decision-making technique, the Combined Compromise Solution (CoCoSo). The findings suggested that D-FFZN offered a more comprehensive and balanced assessment framework that leads to more accurate and reliable decision outcomes. Sensitivity analysis demonstrated that small changes in the parameter value produced minor alterations in the ranking order of alternatives but the D-FFZN model provided a robust optimal solution regardless, thus proving its sturdiness. These findings indicate that the D-FFZN technique has a potential to substantially improve urban land-use planning by equipping stakeholders, policymakers, and urban planners with invaluable guidance in selecting optimal and sustainable development alternatives.

Authors

Institutions

Publication Details

Journal
IEEE Access
Published
2025-01-01
DOI
https://doi.org/10.1109/access.2025.3560685
Primary Topic
Varied Academic Research Topics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimize Decision Model for Urban Land Development Using Disc Fermatean Fuzzy Information With Z-Numbers

Yangjun Pi, Zhenyu Liu, Wei Xia
IEEE Access
Varied Academic Research Topics
article

Optimize Decision Model for Urban Land Development Using Disc Fermatean Fuzzy Information With Z-Numbers

Yangjun Pi, Zhenyu Liu, Wei Xia
article en

Abstract

Urban land development choices manifest complex, ambiguous situations where multiple criteria are involved, making it hard for traditional evaluation methods to address them effectively. The present study introduces an advanced methodological view called the Disc Fermatean Fuzzy Z-Number (D-FFZN) method developed to enhance the accuracy and reliability of urban planning decisions by skillfully addressing uncertainties. The D-FFZN approach was applied in the selection of optimal land development alternatives in a case study through newly formulated aggregation operators based on the weighted averaging and weighted geometric methods. To confirm the method’s performance, a comparative analysis was undertaken between the D-FFZN method and a more renowned multi-criteria decision-making technique, the Combined Compromise Solution (CoCoSo). The findings suggested that D-FFZN offered a more comprehensive and balanced assessment framework that leads to more accurate and reliable decision outcomes. Sensitivity analysis demonstrated that small changes in the parameter value produced minor alterations in the ranking order of alternatives but the D-FFZN model provided a robust optimal solution regardless, thus proving its sturdiness. These findings indicate that the D-FFZN technique has a potential to substantially improve urban land-use planning by equipping stakeholders, policymakers, and urban planners with invaluable guidance in selecting optimal and sustainable development alternatives.

IEEE AccessVol. 13
China University of Geosciences (CN), Wuhan Business University (CN), South China University of Technology (CN)
Sustainable cities and communities
Openalex Percentile: Top 89%
Varied Academic Research Topics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.