Aviation Accident Analysis

Purpose of this project is to analyze civil aviation accidents and predict the damage.

About Data

Analysis & Predictions

Flying has been the go-to mode of travel for years now; it is time-saving, affordable, and extremely convenient. According to the FAA, 2,781,971 passengers fly every day in the US, as in June 2019. Passengers reckon that flying is very safe, considering strict inspections are conducted and security measures are taken to avoid and/or mitigate any mishappenings. However, there remain a few chances of unfortunate incidents. Machine learning Alogrithms Random forest and Logistic regression to find a best fit model for predicting some of the aspects of an accident. These are the best Alogrithms applied to each predictions:
Investigation Type Prediction: Random forest
Aircraft Damage Prediction: Random forest
Accident Severity: Logistic regression

Conatct Us

Name: Tejal Kotkar
Email: kotkar.tejal@gmail.com
LinkedIn: Tejal Kotkar
Name: Savita Hirilall
Email: talktosavita@gmail.com
LinkedIn: Savita Hirilall
Name: Hibo Dahir
Email: sdahir492@gmail.com
LinkedIn: Hibo Dahir
Name: Tana Larson
Email: tana.larson4@outlook.com
LinkedIn: Tana Larson