Abstract
The prediction of environmental variables is important because it facilitates understanding the processes in real time. The objective of this study was to formulate a fuzzy model of four environmental input variables, namely temperature, UV radiation, humidity and wind speed, and two environmental output variables, namely THSW index and electric field. The Mandani fuzzy method was used with 80 fuzzy rules concatenated with the “and” conector defuzzifying the THSW index and the electric field with 19 654 records. The fuzzy model was based on a maximum temperature for 2019 of 29.8 °C with an average of 24.595 °C and a maximum UV radiation of 11.7 and an average of 1.9506 nm, as well as an average humidity of 6.317%, in addition to a wind speed of 12.90 m/s resulting lower in spring with an average of 1.2727 m/s. Likewise, an average THSW index of 25.169 was obtained as output, measured with four meteorological variables with a minimum of 21.055 in spring and a maximum of 25.169 in summer. In addition, an average electric field of −1.6218 kV/m was found in winter and in summer 2019, a value of 0.1682 kV/m was obtained with a minimum value of –6.6993 kV/m and a maximum value of 3.6323 kV/m.
Robustness of the Fuzzy model was determined with the Friedman test, where the THSW index had a value of 0.0014 and the electric field had a value of 0.0021, which shows a good performance of the proposed model.
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Soria, J.J., Poma, O., Sumire, D.A., Rojas, J.H.F. (2021). Fuzzy Model with Meteorological Variables for the Determination of the THSW Index and the Electric Field in the Area of East Lima, Peru. In: Silhavy, R. (eds) Artificial Intelligence in Intelligent Systems. CSOC 2021. Lecture Notes in Networks and Systems, vol 229. Springer, Cham. https://doi.org/10.1007/978-3-030-77445-5_49
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