{"id":19967649,"url":"https://github.com/oaslananka/earthquakepredictionml","last_synced_at":"2026-05-13T00:04:25.354Z","repository":{"id":241877076,"uuid":"808093534","full_name":"oaslananka/EarthquakePredictionML","owner":"oaslananka","description":"A Machine Learning Project for Predicting Earthquake Magnitudes and Occurrences example.","archived":false,"fork":false,"pushed_at":"2024-05-30T12:07:54.000Z","size":152,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-01-12T08:44:17.537Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/oaslananka.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-05-30T11:20:38.000Z","updated_at":"2024-09-19T15:31:49.000Z","dependencies_parsed_at":"2024-05-30T13:18:51.587Z","dependency_job_id":"c3ce2a7b-3516-43d0-b35c-1d6537c5a240","html_url":"https://github.com/oaslananka/EarthquakePredictionML","commit_stats":null,"previous_names":["oaslananka/earthquakepredictionml"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/oaslananka%2FEarthquakePredictionML","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/oaslananka%2FEarthquakePredictionML/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/oaslananka%2FEarthquakePredictionML/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/oaslananka%2FEarthquakePredictionML/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/oaslananka","download_url":"https://codeload.github.com/oaslananka/EarthquakePredictionML/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":241404206,"owners_count":19957650,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-11-13T02:43:22.490Z","updated_at":"2026-05-13T00:04:20.325Z","avatar_url":"https://github.com/oaslananka.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Earthquake Prediction using Machine Learning\n\nThis project aims to predict earthquake magnitudes and occurrences using machine learning models.\n\n## Project Structure\n\n```ini {\"id\":\"01HZ4MWPV1WXE217FHBXMVKS0E\"}\nearthquake-prediction-ml/\n├── data/\n│   └── earthquake_data.csv\n├── src/\n│   └── main.py\n├── README.md\n├── LICENSE\n└── requirements.txt\n```\n\n## Installation\n\n1. Clone the repository:\n\n```sh {\"id\":\"01HZ4MWPV22SCECAA8RZ3TFA9H\"}\ngit clone https://github.com/oaslananka/EarthquakePredictionML.git\ncd EarthquakePredictionML\n```\n\n2. Install the dependencies:\n\n```sh {\"id\":\"01HZ4MWPV22SCECAA8S2CKJ758\"}\npip install -r requirements.txt\n```\n\n## Usage\n\n1. Run the main script:\n\n```sh {\"id\":\"01HZ4MWPV22SCECAA8S41S7ZCC\"}\npython src/main.py\n```\n\n## Data Source\n\nThe earthquake data is fetched from the USGS (United States Geological Survey) API. The data includes information about earthquake magnitudes, locations, depths, and times.\n\n## Algorithms and Methods\n\nThis project uses several machine learning algorithms for earthquake prediction, including:\n\n- Random Forest Regressor\n- Gradient Boosting Regressor\n- XGBoost Regressor\n\nThe models are trained using features engineered from the raw earthquake data, such as statistical measures, zero-crossings, peak counts, FFT values, and the Hilbert transform's amplitude envelope.\n\n## Example Project\n\nThis project serves as an example of using machine learning techniques for predicting natural events. It demonstrates data fetching, preprocessing, feature engineering, model training, and prediction.\n\n## License\n\nThis project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Foaslananka%2Fearthquakepredictionml","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Foaslananka%2Fearthquakepredictionml","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Foaslananka%2Fearthquakepredictionml/lists"}