Adaptive Fuzzy Interference System for Quantifying the Effect of Urban Green Space on Human Health
Abstract
Urban green areas consist of intentionally preserved plantations, parks, and natural elements available to the public for recreation and relaxation. These places are good for people’s health because they provide places that encourage physical activity, stress relief, and mental recovery. To evaluate their influence, urban green areas must be systematically categorised based on their measurable impact on human health. In this research, an Effect Quantifying Process using a Fuzzy Inference System (EQP-FIS) is used to figure out what effect this has by looking at two main factors: health improvements that have been shown to happen and the functional effect of being close to green spaces. The method finds the degree of connectivity between environmental effects and health-related recommendations. Low connectivity indicates limited health benefits, prompting targeted suggestions for improvement, whereas high connectivity supports the growth or replication of effective green spaces. The model’s performance is verified using recommendation scores, effect rates, data availability, and analysis time.
© 2026 Shuting Yan, Lei Shi, Yang Tan, Mengjia Chen, Runjiao Liu, Li Wang, published by Society of Ecological Chemistry and Engineering
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