Call for Papers : Volume 15, Issue 11, November 2024, Open Access; Impact Factor; Peer Reviewed Journal; Fast Publication

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PREDICTION OF THE ELECTRICAL RESISTIVITY OF SOILS IN TROPICAL AREAS BASED ON METEOROLOGICAL VARIABLES USING GENETIC ALGORITHMS AND FUZZY INFERENCE SYSTEM APPROACHES

The safety of property and people against risks and electrical faults is essentially ensured by an earthing system. The essential element of the latter is the electrical resistivity of the soil. This is influenced by several factors. In this work, we used the georeference coordinates of the point (A), state of nature the day before the measurement (B), state of nature on the day of the measurement (C), and the ambient temperature at the measurement point (D). 9513 in-situ measurement samples on selected sites in Lomé constitute the database. Genetic algorithms and fuzzy inference systems made it possible to create models taking into account the bibliographic review. Evaluation criteria such as: RMSE, RRMSE, MAPE and R² are used to evaluate these models. The results give RMSE = 16.20%, RRMSE = 10.94%, MAPE = 9.27%, R² = 97.93% for Genetic Algorithms with the BCD configuration and for fuzzy inference systems, we have RMSE = 71.48, RRMSE = 48.29%, MAPE =35.29%, R² =61.53% by ACD configuration. We conclude that Genetic Algorithms give a very good result given the value of its correlation coefficient with the BCD combination, which justifies that the parameters used are well suited to predicting the electrical resistivity of the soil in the area considered.

Author: 
APALOO BARA Komla Kpomonè, EKEGNON Komi Ghislain, PALANGA Eyouleki Tcheyi G. and BEDJA Koffi-Sa
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Journal Area: 
Physical Sciences and Engineering