Introduction To enhance the precision of evaluating the impact of urban environments on
resident health, this study introduces a novel fuzzy intelligent computing model designed to …

A fuzzy synthetic model combined with risk scores contour was developed for indoor air
quality (IAQ) assessment and management of office building. This research makes up for the …

Cities have become the most important habitats for mankind in most regions of the world.
Many researchers and organizations have attempted to evaluate the states of cities from the …

Characterizing the spatial variation of traffic-related air pollution has been and is a long-
standing challenge in quantitative environmental health impact assessment of urban …

This study aimed to improve the uncertainty in spatial data of risk assessment through a
Fuzzy inference system (FIS) as a way to conduct an environmental risk map of air pollution …

As population density increases, environmental hygiene and public health become
increasingly severe. As the space where residents stay for the longest time and have the …

Predicting future urban health status is significant in terms of identifying urban diseases and
urban planning. Current studies have focused on using machine learning and deep learning …

Air quality levels do not just affect climate change; rather, it leaves a significant impact on
public health and wellbeing. Indoor air pollution is the major contributor to increased …

In smart cities, air pollution has detrimental impacts on human physical health and the
quality of living environment. Therefore, correctly predicting air quality plays an important …

Introduction With the increase of urban population density, urban sanitation becomes more
severe; urban sanitation has important influence on public health. Therefore, in order to …