Applications of Business Analytics in Predicting Flight On-time Performance in a Complex and Dynamic System

Truong, Dothang; Friend, Mark A.; Chen, Hongyun

doi:10.5325/transportationj.57.1.0024

Cited by 14 publications

(5 citation statements)

References 22 publications

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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%

Impacts of Daily Travel by Distances on the Spread of COVID-19: An Artificial Neural Network Model

Truong

2022

Transportation Research Record: Journal of the Transportation R

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The continued spread of COVID-19 poses significant threats to the safety of the community. Since it is still uncertain when the pandemic will end, it is vital to understand the factors contributing to new cases of COVID-19, especially from the transportation perspective. This paper examines the effect of the United States residents’ daily trips by distances on the spread of COVID-19 in the community. The artificial neural network method is used to construct and test the predictive model using data collected from two sources: Bureau of Transportation Statistics and the COVID-19 Tracking Project. The dataset uses ten daily travel variables by distances and new tests from March to September 2020, with a sample size of 10,914. The results indicate the importance of daily trips at different distances in predicting the spread of COVID-19. More specifically, trips shorter than 3 mi and trips between 250 and 500 mi contribute most to predicting daily new cases of COVID-19. Additionally, daily new tests and trips between 10 and 25 mi are among the variables with the lowest effects. This study’s findings can help governmental authorities evaluate the risk of COVID-19 infection based on residents’ daily travel behaviors and form necessary strategies to mitigate the risks. The developed neural network can be used to predict the infection rate and construct various scenarios for risk assessment and control.

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Section: Resultsmentioning

confidence: 96%

Impacts of Daily Travel by Distances on the Spread of COVID-19: An Artificial Neural Network Model

Truong

2022

Transportation Research Record: Journal of the Transportation R

Self Cite

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“…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%

Research Opportunities to Improve the Competitiveness by Using Network Project Teams

Новиков¹,

Komarova²,

Dadyan³

2020

RWE

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This article shows the relevance of the problem of increasing the competitiveness of Information Technology (IT) companies as part of the fourth industrial revolution and presents the relevance of the implementation of network project teams to improve the competitiveness of IT companies. The paper presents the hypothesis, purpose, object and subject of research and shows the practical significance and novelty of the work. There are possibilities of increasing the competitiveness of IT companies in the framework of the aerospace industry. The paper presents the industry's need for automated systems required for air transportation. We can find the correlation of the emergence of new management tasks with the presence of such components as new management standards, the growth of the number of holdings, financial and industrial groups and the total number of enterprises. It presents the advantages of using network project teams for solving complex and non-standard tasks within a limited time resource. Furthermore, it shows a comparison of the two approaches using the network and conventional project team. It is shown that the usual project team does not have the capabilities that will ensure the high competitiveness of the company in the implementation of complex, non-standard projects, where it is impossible to do without new knowledge and competencies and complete the project in a limited time. Also, it describes the process of transformation of an ordinary group into a network structure. Also, this article also illustrates possibility to avoid many negative characteristics of a conventional group while maintaining the basic principles of the project team and its positive characteristics.

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“…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%

Empirical decision analytics approach of advanced granularity-based models for identifying performance measures of ERPS application

Chen

White

2018

J Supercomput

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There are four motivations in this study. First, recent machine learning techniques, such as decision trees, multi-layer perceptron, and Bayesian methods, for empirical decision analytics approach are spanning a wide research interest to understand and solve a real-world complex problem and thus attract significant concerns for identifying performance measures of extensive application domains. Second, integrated circuit design (IC) industry in Taiwan plays a prominent bellwether in triggering world's economic markets, particularly for Taiwan Semiconductor Manufacturing Company. Third, enterprise resource planning system (ERPS) has been one of the most popular tools in total solution management across industries, and its relevant decision rules attract current trends in using an advanced soft computing approach. Lastly, with limited literature reviews, there is scarce investigation on picking right ERPS with effective decision rule-based knowledge for the IC design industry from application perspectives, and this research is first to bridge such a study gap for technical and managerial applications. Thus, this research synthesizes and proposes an advanced hybrid procedure to organize multi-expert granularity-based models with comprehensible decision rule-based wisdom to experience the ERPS selection and identify its determinants. The study finding implies that the determinants are varied from the class types and benefit interested parties useful references to facilitate positive migration of inter-industry. This research significantly contributes clear motivation and originality with good application values for an advanced hybrid analysis.

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Applications of Business Analytics in Predicting Flight On-time Performance in a Complex and Dynamic System

Cited by 14 publications

References 22 publications

Impacts of Daily Travel by Distances on the Spread of COVID-19: An Artificial Neural Network Model

Impacts of Daily Travel by Distances on the Spread of COVID-19: An Artificial Neural Network Model

Research Opportunities to Improve the Competitiveness by Using Network Project Teams

Empirical decision analytics approach of advanced granularity-based models for identifying performance measures of ERPS application

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