Fuzzy inference algorithm for quantifying thermal comfort in peri-urban environments
Environment, Development and Sustainability, ISSN: 1573-2975
2024
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
The alteration of the landscape due to urban concentration can bring effects such as “heat islands” that affect human well-being. The objective was to apply mathematical modeling and ambiance methods to build a classifier based on fuzzy logic that represents different levels of human well-being resulting from the peri-urban transitional area. The specific objectives were to compare different landscapes and their levels of comfort, using the human thermal comfort index and converting RGB images into Ground-Truth annotations to calculate the percentage of landscape elements and determine their influence on the thermal environment. The research consisted in the construction of a mathematical model in which the input variables were the Human Discomfort Index (HDI) and the type of coverage of the area, with the output variable being Human Well-Being (HWB). The model test was carried out with data from field research in the municipality of Dourados, located in the state of Mato Grosso do Sul, Brazil. For the construction of the classifier, pre-trained models with python libraries and Ground-Truth annotations programmed in HTML were used to observe each component in space, being possible to qualify their degrees of relevance by the Mamdani inference method. Defuzzification was performed using the Center of Gravity method, transforming the fuzzy set into a numerical set. The nine environments/microclimates (1A, 1B, 1C; 2A, 2B, 2C; 3A, 3B, 3C) used to test the model presented Uncomfortable or Stressful HDI after 11:00 am and the classifier perfectly represented all the simulations proposed by the operator. The most stressful environment was the asphalt pavement and the best with the inclusion of trees. The fuzzy model demonstrated effectiveness in predicting human well-being based on the collected environmental variables, validating the simulator as a support tool for urban management and allowing adjustments in environmental conditions. The analysis of field data confirmed that vegetation improves thermal comfort in peri-urban zones and mitigates heat islands, reinforcing the importance of urbanization policies that prioritize the inclusion of tree-covered areas.
Bibliographic Details
Springer Science and Business Media LLC
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know