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@article{151753,
        author = {Vishrut Raj and Viran Raj and Satyam Singh and Adityanath Mishra},
        title = {FLIGHT DELAY PREDICTION},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {1},
        pages = {816-820},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=151753},
        abstract = {light delay prediction is fundamental to establish the more efficient airline business. The development of accurate prediction models for flight delays became cumbersome due to the complexity of air transportation system, the number of methods for prediction, and the deluge of flight data. In this context, this paper presents a thorough literature review of approaches used to build flight delay prediction model. Airlines delays make immense loss for business field as well as in budget loss for a country. Flight delays hurt airlines, airports, and passengers. We are proposing machine learning algorithms like Linear regression Techniques. The aim of this research work is to predict Flight Delay, Which is highest economy producing field for many countries and among many transportation this one is fastest and comfort, so to identify and reduce flight delays, can dramatically reduce the flight delays to saves huge amount of turnovers, using machine-learning algorithms. Flight delays could always be annoying, especially in the case when the period of delay was so long that there was even a danger to miss the next flight. However, if there was a way to predict whether there would be a delay or even better – how long the delay could be, then people could make earlier preparation to reschedule following flights in an earlier manner. },
        keywords = {Data prediction, Machine Learning, Linear Regression Techniques},
        month = {},
        }