Redirigiendo al acceso original de articulo en 16 segundos...
Inicio  /  Applied Sciences  /  Vol: 14 Par: 3 (2024)  /  Artículo
ARTÍCULO
TITULO

Prediction and Analysis of Airport Surface Taxi Time: Classification, Features, and Methodology

Jianan Yin    
Mingwei Zhang    
Yuanyuan Ma    
Wei Wu    
He Li and Ping Chen    

Resumen

Airport arrival and departure movements are characterized by high dynamism, stochasticity, and uncertainty. Therefore, it is of paramount importance to predict and analyze surface taxi time accurately and scientifically. This paper conducts a comprehensive review of existing studies on surface taxi time prediction and analysis. Firstly, the overall research framework of surface taxi time prediction and analysis is categorized from three perspectives: taxi time type, movement type, and modeling method. Then, focusing on the two means of taxi time analytical modeling and simulation modeling, the existing mainstream models and methods are categorized, and the main ideas and scope of application of the various methods are analyzed. Finally, the paper presents the future development direction of surface taxi time prediction prospects. The research results are aimed at providing basic support and methodological guidance for reducing the uncertainty in airport surface operation and enhancing the level of control and decision-making ability of airport surface operation.

 Artículos similares

       
 
Haibo Chu, Zhuoqi Wang and Chong Nie    
Accurate and reliable monthly streamflow prediction plays a crucial role in the scientific allocation and efficient utilization of water resources. In this paper, we proposed a prediction framework that integrates the input variable selection method and ... ver más
Revista: Water

 
Ilia Zaznov, Julian Martin Kunkel, Atta Badii and Alfonso Dufour    
This paper introduces a novel deep learning approach for intraday stock price direction prediction, motivated by the need for more accurate models to enable profitable algorithmic trading. The key problems addressed are effectively modelling complex limi... ver más
Revista: Applied Sciences

 
Shurong Peng, Lijuan Guo, Yuanshu Li, Haoyu Huang, Jiayi Peng and Xiaoxu Liu    
The allocation of biogas between power generation and heat supply in traditional kitchen waste power generation system is unreasonable; for this reason, a biogas prediction method based on feature selection and heterogeneous model integration learning is... ver más
Revista: Applied Sciences

 
Nosa Aikodon, Sandra Ortega-Martorell and Ivan Olier    
Patients in Intensive Care Units (ICU) face the threat of decompensation, a rapid decline in health associated with a high risk of death. This study focuses on creating and evaluating machine learning (ML) models to predict decompensation risk in ICU pat... ver más
Revista: Algorithms

 
Leon Kopitar, Iztok Fister, Jr. and Gregor Stiglic    
Introduction: Type 2 diabetes mellitus is a major global health concern, but interpreting machine learning models for diagnosis remains challenging. This study investigates combining association rule mining with advanced natural language processing to im... ver más
Revista: Information