Analyzing Machine Learning Techniques for Air Passenger Numbers Forecasting-Reference-Cited by-同舟云学术

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Analyzing Machine Learning Techniques for Air Passenger Numbers Forecasting

Published:2024-06-19 Issue: Volume:31 Page:107-112
ISSN:
Container-title:2024 21st International Joint Conference on Computer Science and Software Engineering (JCSSE)
language:
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Author:

Khumla Pornsiri¹,Sarawan Kamthorn²,Polpinij Jantima³,Gonwirat Sarayut²,Chantima Phoori²,Sommool Worapot²

Affiliation:

1. Technology Kalasin University,Faculty of Engineering and Industrial,Department of Logistics Engineering and Transportation Technology,Kalasin,Thailand

2. Technology Kalasin University,Faculty of Engineering and Industrial,Department of Computer Engineering,Kalasin,Thailand

3. Mahasarakham University,Faculty of Informatics,Department of Computer Science,Mahasarakham,Thailand

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10613603/10613624/10613714.pdf?arnumber=10613714

Reference31 articles.

1. Ministry of Transport,2023

2. A Novel Approach to Air Passenger Index Prediction: Based on Mutual Information Principle and Support Vector Regression Blended Model

3. Air passenger forecasting using Neural Granger causal Google trend queries

4. A COMPARATIVE ANALYSIS OF MACHINE LEARNING ALGORITHMS FOR THE PURPOSE OF PREDICTING NORWEGIAN AIR PASSENGER TRAFFIC

5. Air passenger demand forecast through the use of Artificial Neural Network algorithms

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