A Mamdani-Based Fuzzy Logic Model for Evaluating the Design Quality of Urban Squares

Abstract

Urban squares are essential elements defining public interactions, cultural manifestations, and urban social characteristics. The spaces function as central meeting areas where citizens participate in civic duties, connect and serve maintain urban design unity. The evaluation process of design quality proves challenging because it combines the personal interpretation of many complex variables, which standard assessment techniques struggle to measure. The researchers present a Mamdani-based fuzzy logic model that evaluates urban square design quality through eight core parameters: imageability, meaning, legibility, time, enclosure, dominance, diversity, and comfort. Fuzzy logic is an approximation system that converts evaluative statements based on linguistic expressions into numerical arrangements, which excel at interpreting multifaceted urban design evaluations. The model underwent calibration through evaluations from 1,044 architecture professionals, planners, and landscape architects, and it was used to analyze 20 internationally recognized urban squares with various spatial designs across different cultural settings. The quantitative model demonstrated its accuracy by matching expert-aggregated scores when measured against predictions, with a precision of +/- 1.5% pin predicting outcomes. All examined variables confirmed that enclosure and comfort are the key factors influencing perceptions of design quality. The model provides practical applications for urban planners, decision-makers, and educators through its ability to create a standardized evaluation process for current and future urban interventions. The framework offers a distinctive approach that integrates design thinking-oriented methods with evaluative measures, rendering it practical for contemporary urban design practice.