2018
DOI: 10.5325/transportationj.57.1.0024
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Applications of Business Analytics in Predicting Flight On-time Performance in a Complex and Dynamic System

Abstract: Flight on-time performance is one of the most important issues in the National Airspace System, a very complex and dynamic system. To avoid negative impacts to the aviation industry, the Federal Aviation Administration has set a long-term objective of understanding and mitigating flight delays. Building an effective and accurate prediction model of flight-delay incidents will help airport executives make the best decisions in delay scenarios. This article utilized two advanced prediction methods to predict the… Show more

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Cited by 14 publications
(5 citation statements)
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“…The model performance evaluation shows the sum of squares error for this ANN model is 3.613, which is relatively low, given the mean and standard deviation of the target variable are 655 and 1,309, respectively. In addition, the relative error is 0.178; that is, the ANN model is able to explain about 82.2% of variances of the target variable based on the predictors, indicating a good predictive power of the model ( 21 , 30 ). Figure 5 shows the predicted by observed chart, indicating the ANN model predicts well most cases with relatively high accuracy.…”
Section: Resultsmentioning
confidence: 96%
“…The model performance evaluation shows the sum of squares error for this ANN model is 3.613, which is relatively low, given the mean and standard deviation of the target variable are 655 and 1,309, respectively. In addition, the relative error is 0.178; that is, the ANN model is able to explain about 82.2% of variances of the target variable based on the predictors, indicating a good predictive power of the model ( 21 , 30 ). Figure 5 shows the predicted by observed chart, indicating the ANN model predicts well most cases with relatively high accuracy.…”
Section: Resultsmentioning
confidence: 96%
“…Agencies that work with air content and sales of additional services use tools, including such systems as: The emergence of new management tasks associated with the presence of such components as new management standards, financial reporting, analysis and business planning, project management, necessitates the creation of new tools (Truong, Friend & Chen, 2018). The increase in the number of holdings, financial and industrial groups and the grow in the total number of enterprises in different industries causes the multiplication of the volume of information flows and the increase in the requirements for the level and degree of automation.…”
Section: Methodsmentioning
confidence: 99%
“…In particular, DTs in ML fields are one of the well algorithms and have a satisfactory result in classification community. It is built from a set of instances of the correction between some symbolic or numerical inputs (e.g., conditional-attributes) and one symbolic output (e.g., decisional-attribute) and is extensively used in various application fields, such as data mining applications, statistical data analysis, and other industry services [53]. Thus, the DTs-based feature selection is focused on this research.…”
Section: Significant Contribution and Originality Of Application Valuesmentioning
confidence: 99%