{"id":17695660,"url":"https://github.com/narenkhatwani/bird-strike-analysis","last_synced_at":"2025-03-30T23:44:30.700Z","repository":{"id":148856578,"uuid":"314612977","full_name":"narenkhatwani/Bird-Strike-Analysis","owner":"narenkhatwani","description":"The aim of our project is to analyze past years' bird strike data with respect to the phase of flight, time of day, pilot warning status, and various other parameters. ","archived":false,"fork":false,"pushed_at":"2021-04-19T11:28:25.000Z","size":28337,"stargazers_count":0,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-06T05:18:24.000Z","etag":null,"topics":["analysis","bird","bird-strike","birds","linear-regression","linear-regression-models","linear-regression-python","machine-learning","python","sql"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/narenkhatwani.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2020-11-20T16:44:16.000Z","updated_at":"2021-04-19T11:29:11.000Z","dependencies_parsed_at":null,"dependency_job_id":"9e8c7d45-090c-4b67-aaa9-c61ef8192c04","html_url":"https://github.com/narenkhatwani/Bird-Strike-Analysis","commit_stats":{"total_commits":4,"total_committers":1,"mean_commits":4.0,"dds":0.0,"last_synced_commit":"8f43ef874dd6d691f8968057c135a23e798f0db5"},"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/narenkhatwani%2FBird-Strike-Analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/narenkhatwani%2FBird-Strike-Analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/narenkhatwani%2FBird-Strike-Analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/narenkhatwani%2FBird-Strike-Analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/narenkhatwani","download_url":"https://codeload.github.com/narenkhatwani/Bird-Strike-Analysis/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246395572,"owners_count":20770240,"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":["analysis","bird","bird-strike","birds","linear-regression","linear-regression-models","linear-regression-python","machine-learning","python","sql"],"created_at":"2024-10-24T14:06:29.488Z","updated_at":"2025-03-30T23:44:30.678Z","avatar_url":"https://github.com/narenkhatwani.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Bird-Strike-Analysis\n\n## About this Project\n\n**1.Introduction:**\n\n**1.1 Introduction to the project**\n\nA bird Strike can be defined as a collision between a bird species and the aircraft engine . A bird\nstrike can result in various mishaps such as crash landing of aircraft or an aircraft getting stalled\nwhich may lead to some unavoidable circumstantial landing situations. In order to prevent such\nmishaps from happening in the near future we propose an idea of predicting future bird strikes\nand analysis of the previous years data of bird strikes. The data of the previous years will be\nanalysed and will help in improving the accuracy of prediction of bird strikes that might occur\nover the period of next five years. The prediction and analysis would be based on the parameters\nsuch as phase of flight, period of the day or altitude. Numerous other parameters like bird species\nand size of bird species can also be analysed through which there can be a pattern established\nwhich will not only help us understand the birds’ migration route but also help prevent any bird\nstrikes in future. The prevention of bird strikes through prior prediction can save a lot of lives\nthat might be at stake. The algorithms that can be used for prediction would be linear regression,\nrandom forest algorithm and time series analysis.\n\n**1.2 Motivation**\n\nMotivation for any project is not just needed by a single team member. It is a joint effort which\nhas to be taken by each member of a project team. Similarly in our project, each of the team\nmembers wanted to give something back to the society and we all collectively decided that civil\naviation is an industry which is booming a lot in current times, however it also needs\nadvancements in the direction of bird strike prevention as it is type of incident that needs\nconstant attention, since it not only compromises the aircraft safety but also leads to loss of\nwildlife.\n\n**1.3 Problem Definition**\n\nThe aim of our project is to analyze past years bird strike data with respect to phase of flight,\ntime of day, pilot warning status and various other parameters.The model will make predictions\nabout the occurrence of bird strikes in future years in order to make important decisions to avoid\nfuture occurrences of bird strikes.\n\n**1.4 Relevance of the project**\n\nFor the aviation industry, aircraft and passenger safety is of utmost importance. Bird strikes pose\na threat to the same. Therefore, a system that predicts the occurrence of these bird strikes and\n\nanalyses the parameters that affect their occurrence would be of great assistance to the aviation\nindustry in preventing future bird strikes, thereby increasing flight safety.\n\n**1.5 Methodology used:**\n\nThe main objective of the methodology applied is to analyze the Bird Strike data obtained from\nKaggle by a Data Scientist at Travelport Atlanta, Georgia, United States and use it for the\nbetterment of passengers as our vision is to make the Air traffic controllers aware of the\nadvancement in technology which can benefit them in not only increasing the rate of avoiding\nbird strike occurrences but also give them the opportunity to increase the probity among the\ncommunity of passengers and airlines . The databases for both the survey results have been\nprovided for further study. It aims to take crucial decisions in the aviation industry related to the\nflight plans.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnarenkhatwani%2Fbird-strike-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnarenkhatwani%2Fbird-strike-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnarenkhatwani%2Fbird-strike-analysis/lists"}