@ARTICLE{Said_Sri_Mawar_Prediction_2021,
 author={Said, Sri Mawar and Nappu, Muhammad Bachtiar and Asri, Andarini and Utomo, Bayu Tri},
 volume={vol. 70},
 number={No 3},
 journal={Archives of Electrical Engineering},
 pages={499-511},
 howpublished={online},
 year={2021},
 publisher={Polish Academy of Sciences},
 abstract={Lightning is one of the causes of transmission disorders and natural phenomena that cannot be avoided. The South Sulawesi region is located close to the equator and has a high lightning density. This condition results in lightning susceptibility of disturbances to electrical system lines, especially in high-voltage airlines and substations. An Adaptive Neuro-Fuzzy Inference System (ANFIS) will show the Root Mean Square Error (RMSE) based on the membership function type. This journal is to predict the value of the transmission tower lightning density using the ANFIS method. The value of the lightning strike density index can later be determined based on ANFIS predictions. Analysis of the value calculation system of structural lightning strikes in the South Sulawesi region of the Sungguminasa-Tallasa route can be categorized as three characteristics lightning density (Nd). The calculation system results for the value of structural lightning struck in the South Sulawesi region and validated between manual calculations and ANFIS with an average percentage of 0.0554%.},
 type={Article},
 title={Prediction of lightning density value tower based on Adaptive Neuro-fuzzy Inference System},
 URL={http://journals.pan.pl/Content/120515/art01_corr.pdf},
 doi={10.24425/aee.2021.137570},
 keywords={Adaptive Neuro-fuzzy Inference System, lightning density prediction tower, Transmission Line Arrester},
}