Forecasting Models for Non-Scheduled Air Transportation: Statistical Analysis, Machine Learning Methods and Hybrid Forecasting Approaches - Image 1

£66.00

LAP Lambert Academic Publishing Forecasting Models for Non-Scheduled Air Transportation: Statistical Analysis, Machine Learning Methods and Hybrid Forecasting Approaches

Name: Forecasting Models for Non-Scheduled Air Transportation: Statistical Analysis, Machine Learning Methods and Hybrid Forecasting Approaches
Brand: LAP Lambert Academic Publishing
Price: 66.0 GBP
Availability: InStock

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Description

This book focuses on the development and application of modern forecasting models for non-scheduled passenger air transportation. Several quantitative approaches are analyzed, including regression models, ARIMA stochastic models, Support Vector Machine (SVM) methods, fuzzy forecasting models, and hybrid forecasting techniques. The research presented in this book aims to analyze the effectiveness of different forecasting approaches and to identify models that provide higher forecasting accuracy. The findings may be useful for researchers, aviation specialists, transport analysts, and students interested in aviation systems and forecasting methods.

Product Specifications

Brand: LAP Lambert Academic Publishing
Format: paperback
ASIN: 6209788076
Category: Books > Subjects > Business, Finance & Law > E-Commerce > E-commerce
Domain: Amazon UK
Release Date: 12 March 2026
Listed Since: 04 April 2026

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LAP Lambert Academic Publishing Forecasting Models for Non-Scheduled Air Transportation: Statistical Analysis, Machine Learning Methods and Hybrid Forecasting Approaches

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