Air Passenger Demand Forecasting for Airports: Use of Neural Networks and Regression Analysis with Case Studies of planned Zafer and Or-Gi Airports in Turkey

Description

This book is focused on establishing demand forecasting models to a highly uncommon transportation problem: Air Passenger Demand Forecasting for Airports. This problem has unique features as lack of past data, data with high statistical noise, missing data and similar real-life problems.This study maybe useful for students, researchers and forecasters who has to establish models with mentioned features. In this work modern forecasting methods and tools were proposed for such solving such complex problems. Also this book can be beneficial for people who are interested in neural networks and neural forecasting models.Transportation professionals may find this work interesting because it focuses on passenger demand and models in this study can be applied to any transportation structure anywhere. Also decision makers of government professionals (especially emerging nations), private investors, banks and large construction companies may find instrumental methods like using socioeconomical indicators for establishing demand models and other similar methods. And finally this book can be useful for anyone who is interested in forecasting and/or transportation in general.