Year: 2024
Type: article
Abstract: As the need for early detection and mitigation of potential threats from near-Earth objects grows, this study presents a comprehensive approach to predicting hazardous asteroids using machine learning techniques. Given the increasing importance of protecting our planet from potential impact events, accurately classifying and predicting hazardous asteroids is cru- cial. The study proposes a comprehensive system for predicting and mitigating asteroid hazards using advanced data processing, machine learning, and simulation techniques. The proposed study collect real-time and historical asteroid data, process and clean this data, extract relevant features, and train machine learning models to predict potentially hazardous asteroids. Additionally, Monte Carlo simulations are employed to assess the collision risks of these asteroids with Earth. A forecasting module predicts future asteroid behavior based on historical and simulated data. The system also includes an alert mechanism that notifies relevant stakeholders when a potentially hazardous asteroid is detected
Authors: Ananya A, Srividya M S
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4404777427