Name: Using Machine Learning Approaches (en Inglés)
Price: 111.96 USD
Availability: InStock
Author: Srisaeng, Panarat ; Baxter, Glenn ; Sampaothong, Parleda
ISBN: 9786205529454

portada Using Machine Learning Approaches (en Inglés)

Using Machine Learning Approaches (en Inglés)

Formato

Libro Físico

Autor

Panarat Srisaeng

Glenn Baxter

Parleda Sampaothong

Editorial

LAP Lambert Academic Publishing

Idioma

Inglés

N° páginas

272

Encuadernación

Tapa Blanda

Dimensiones

22.9 x 15.2 x 1.5 cm

Peso

0.40 kg.

ISBN13

9786205529454

Categorías

Tecnología aeroespacial y aeronáutica
Astronáutica

Using Machine Learning Approaches (en Inglés)

Panarat Srisaeng (Autor) · Glenn Baxter (Autor) · Parleda Sampaothong (Autor) · LAP Lambert Academic Publishing · Tapa Blanda

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Reseña del libro "Using Machine Learning Approaches (en Inglés)"

Highly accurate and reliable passenger air travel demand forecasts are critical for airports as they are a key input into airport master plans and they are also used to guide management decisions on airport design and infrastructure planning, airport operations, and resource planning. The objective of this book is to develop and empirically test adaptive neuro-fuzzy inference system (ANFIS) and artificial neural networks (ANNs) to predict airport's passenger demand. The study is based on five major airports: Frankfurt Airport, Hong Kong International Airport, Tokyo's Narita International Airport, Chicago's O'Hare International Airport, and Sydney Kingsford Smith Airport, Australia. The performance of the artificial neural network (ANN) and adaptive neuro-fuzzy inference systems models was assessed by five goodness of fit measures: coefficient of determination (R2), mean absolute error (MAE), mean absolute percentage error (MAPE), and root mean squared error (RMSE). Artificial intelligence-based machine learning modelling techniques are worthy of consideration for those interested in forecasting airport passenger demand.