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原文传递 Florida Aviation Activity Forecast Methodologies and Tools Development.

题名：	Florida Aviation Activity Forecast Methodologies and Tools Development.
作者：	Zhang, Y.; Wu, Z.; Menon, N.
关键词：	Aviation activity forecast tool, ARIMA (Autoregressive Integrated Moving Average), Aviation activity, Airport planning, Autoregressive Integrated Average Model (ARIMA), Monte Carlo simulation, Methodologies, Florida Department of Transportation (FDOT)
摘要：	Aviation activity forecast is a necessary tool in airport planning and financing decisions. It provides inputs for understanding commercial and financial requirements and for decision making in defining future capacity and operational strategies. Accurate forecasts drive appropriate investment policy that will lead to effective investment return and stimulate regional economic development. Nevertheless,the forecast tool currently in use by FDOT was developed years ago, based on basic forecasting methods. This research developed new methodologies for airport activity forecasting and updated the aviation activity forecast function in existing Florida Aviation Database with advanced forecasting methodologies. Specifically, the autoregressive integrated average model (ARIMA) and Monte Carlo simulation were used and corresponding automatic forecasting algorithms were developed after the review of existing methodologies and analysis of their advantages and disadvantages. It is expected that the forecast tool with the new methodologies can provide more insights and better decision support for FDOT personnel making financial and resource allocation decisions.
报告类型：	科技报告