Version 1
: Received: 4 May 2023 / Approved: 5 May 2023 / Online: 5 May 2023 (07:17:49 CEST)
How to cite:
Latifinavid, M.; Balıkçı, C.; Dengiz, S. Aircraft Failures Prediction via Adaptive Neuro-Fuzzy Inference System. Preprints2023, 2023050313. https://doi.org/10.20944/preprints202305.0313.v1
Latifinavid, M.; Balıkçı, C.; Dengiz, S. Aircraft Failures Prediction via Adaptive Neuro-Fuzzy Inference System. Preprints 2023, 2023050313. https://doi.org/10.20944/preprints202305.0313.v1
Latifinavid, M.; Balıkçı, C.; Dengiz, S. Aircraft Failures Prediction via Adaptive Neuro-Fuzzy Inference System. Preprints2023, 2023050313. https://doi.org/10.20944/preprints202305.0313.v1
APA Style
Latifinavid, M., Balıkçı, C., & Dengiz, S. (2023). Aircraft Failures Prediction via Adaptive Neuro-Fuzzy Inference System. Preprints. https://doi.org/10.20944/preprints202305.0313.v1
Chicago/Turabian Style
Latifinavid, M., Cemal Balıkçı and Suat Dengiz. 2023 "Aircraft Failures Prediction via Adaptive Neuro-Fuzzy Inference System" Preprints. https://doi.org/10.20944/preprints202305.0313.v1
Abstract
Safety is very important in aviation since a loss of safety frequently results in both fatalities and financially damaging situations that are typically unrecoverable. Thus, achieving safety as much as possible is the primary goal of practically all aviation technology work. In this study, an Adaptive Neuro-Fuzzy Inference System (ANFIS)-based classifier is created to estimate the fault risk factor of airplanes. Five categories of real fleet data belonging to structure, electrical, avionic, motor systems, and incident statistics of the planes have been used for classifier development. A risk factor determination for each plane is the output of the developed intelligent classifier, and it can be used to identify general overhaul candidate planes and stop defects and crashes before they happen. The obtained results show that using ANFIS provides a great capability in processing many inputs and outputs depending on different types and classes in the aviation industry and thus predicting the failure risk of the airplane efficiently.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
