Construction of Advanced Machine Learning Models for Air Traffic

Construction of Advanced Machine Learning Models for Air Traffic

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This book explores the application of various time series and machine learning techniques to model and forecast domestic airline traffic. It provides a comprehensive study of traditional and modern predictive approaches. It presents an extensive literature review on airline traffic modeling, covering traditional time series methods(Holt's Winter, ARIMA, SARIMA) alongside advanced machine learning techniques(FFNN, MLP, LSTM). A comparative analysis of these methods, highlighting their strengths and limitations, is also included. Further, it explores the Bayesian estimation of SARIMA model param...