Journal ArticleDOI
Machine Learning Approach for Flight Departure Delay Prediction and Analysis
Reads0
Chats0
TLDR
A support vector machine (SVM) model is employed to explore the non-linear relationship between flight delay outcomes and reveals that factors such as pushback delay, taxi-out delay, ground delay program, and demand-capacity imbalance are significantly associated with flight departure delay.Abstract:
The expected growth in air travel demand and the positive correlation with the economic factors highlight the significant contribution of the aviation community to the US economy On‐time operatiread more
Citations
More filters
美聯邦航空廳(Federal Aviation Administration)의 航空機 製作檢査 制度의 現況
TL;DR: The U.S. commercial space launch industry has changed considerably since the enactment of the Commercial Space Launch Amendments Act of 2004 as discussed by the authors, which prohibited FAA from regulating crew and spaceflight participant safety before 2012, a moratorium that was later extended but will now expire on September 30, 2015.
Journal ArticleDOI
Flight delay prediction based on deep learning and Levenberg-Marquart algorithm
Maryam Farshchian Yazdi,Seyed Reza Kamel,Seyyed Javad Seyyed Mahdavi Chabok,Maryam Kheirabadi +3 more
TL;DR: Results of three models on both imbalanced and balanced datasets shows that precision, accuracy, sensitivity, recall and F-measure of SDA-LM model with im balanced and balanced dataset is improvement than SAE-LM and SDA models.
Journal Article
A Non-Dominated Sorting Genetic Algorithm Approach for Optimization of Multi-Objective Airport Gate Assignment Problem
TL;DR: In this article, a three-objective gate assignment problem is formulated as a three objective problem, taking into account all resources and restrictions, which can be directly linked to airport authorities' multiple criteria decision-making processes.
Journal ArticleDOI
Flight Delay Classification Prediction Based on Stacking Algorithm
TL;DR: It is proved that Stacking algorithm has advantages in airport flight delay prediction, especially for the algorithm selection problem of machine learning technology.
Journal ArticleDOI
Social ski driver conditional autoregressive-based deep learning classifier for flight delay prediction
TL;DR: In this paper , the authors proposed a novel alternative method, namely social ski driver conditional autoregressive-based (SSDCA-based) deep learning, which combines the Social Ski Driver algorithm with Conditional Autoregressive Value at Risk by Regression Quantiles.
References
More filters
Journal ArticleDOI
Support-Vector Networks
Corinna Cortes,Vladimir Vapnik +1 more
TL;DR: High generalization ability of support-vector networks utilizing polynomial input transformations is demonstrated and the performance of the support- vector network is compared to various classical learning algorithms that all took part in a benchmark study of Optical Character Recognition.
Journal ArticleDOI
A comparison of methods for multiclass support vector machines
Hsu Chih-Wei,Chih-Jen Lin +1 more
TL;DR: Decomposition implementations for two "all-together" multiclass SVM methods are given and it is shown that for large problems methods by considering all data at once in general need fewer support vectors.
Journal ArticleDOI
A systematic analysis of performance measures for classification tasks
Marina Sokolova,Guy Lapalme +1 more
TL;DR: This paper presents a systematic analysis of twenty four performance measures used in the complete spectrum of Machine Learning classification tasks, i.e., binary, multi-class,multi-labelled, and hierarchical, to produce a measure invariance taxonomy with respect to all relevant label distribution changes in a classification problem.
Journal ArticleDOI
Classification of hyperspectral remote sensing images with support vector machines
Farid Melgani,Lorenzo Bruzzone +1 more
TL;DR: This paper addresses the problem of the classification of hyperspectral remote sensing images by support vector machines by understanding and assessing the potentialities of SVM classifiers in hyperdimensional feature spaces and concludes that SVMs are a valid and effective alternative to conventional pattern recognition approaches.
Journal ArticleDOI
An assessment of support vector machines for land cover classification
TL;DR: An introduction to the theoretical development of the SVM and an experimental evaluation of its accuracy, stability and training speed in deriving land cover classifications from satellite images are given.