Using Big Data Analytics to Create a Predictive Model for Joint Strike Fighter

Norman, Ryan B.; Bolin, Jason; Powell, Edward T.; Amin, Sanket; Nacker, John

doi:10.1109/bigdata.2018.8622388

Cited by 5 publications

(3 citation statements)

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“…BD can also facilitate decision making in military operations. In [57] Norman et al described how commercially tested BD analysis methodologies could help the Joint Strike Fighter program, acquire stronger knowledge management and analysis capabilities for testing and evaluation processes. At the same time, the authors highlighted how these methodologies could also lead to faster and more efficient decision making.…”

Section: Supporting Military Operationsmentioning

confidence: 99%

“…Air traffic flow analysis based on ADS-B BD [33], using air traffic and weather BD for improving strategic planning of airlines [34], trajectory prediction based on surveillance and other BD [35], using flown trajectories BD to calculate flight performance indices [36], and visualization of multiple trajectories, utilizing flight BD [37] Delay Prediction and Resource Allocation Flight delay prediction using multiple ML algorithms [38], flight delay prediction based on ADS-B and other BD [39], BD-based residual airspace resource evaluation methodology [40], and BD-enabled network architecture for AGVNs [41] Maintenance Optimization Optimized maintenance and resource allocation based on BD analytics [42] and improving predictive maintenance by utilizing BD from heterogeneous sources [43] Collecting Customer Insights/Increasing Customer Satisfaction BD-based analysis of customer engagement of a commercial airline [44], linear regression model for predicting flight-related web searches [45], and increasing customer satisfaction and improving aviation service quality by utilizing BD from different sources [46] Solutions for the Industry Improving source localization in industrial facilities by using UAV BD [48] and BD analytics for supply chain efficiency based on UAV BD [49] Solutions for Infrastructures Detection of electrical transmission towers based on BD from UAVs [50], BD-based methodology for optimizing 5G service provisioning from UAVs [51], optimized BD management leading to better disaster management [52], EMS based on BD analytics for minimizing operating costs of UAVs [53], and BD data management optimization in applications with UAV base stations [54] Supporting Military Operations BD analysis for characterizing if an aircraft is commercial or military [55], using ADS-B BD for real time classification of aircrafts [56], and improving knowledge management and analysis for testing and evaluation processes of the Joint Strike Fighter program using BD analysis [57] Increasing Air Force Safety BD-based architecture for improving military flight safety [58], improving military aircrafts' health management systems by utilizing heterogeneous BD …”

Section: Subcategory Specific Applicationmentioning

confidence: 99%

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Applications and Technologies of Big Data in the Aerospace Domain

Adamopoulou

Daskalakis

2023

Electronics

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Over the last few years, Big Data applications have attracted ever-increasing attention in several scientific and business domains. Biomedicine, transportation, entertainment, and aerospace are only a few examples of sectors which are increasingly dependent on applications, where knowledge is extracted from huge volumes of heterogeneous data. The main goal of this paper was to conduct an academic literature review of prominent publications revolving around the application of BD in aerospace. A total of 67 publications were analyzed, highlighting the sources, uses, and benefits of BD. For categorizing the publications, a novel 6-fold approach was introduced including applications in aviation technology and aviation management, UAV-enabled applications, applications in military aviation, health/environment-related applications, and applications in space technology. Aiming to provide the reader with a clear overview of the existing solutions, a total of 15 subcategories were also utilized. The results indicated numerous benefits deriving from the application of BD in aerospace. These benefits referred to the aerospace domain itself as well as to many other sectors including healthcare, environment, humanitarian operations, network communications, etc. Various data sources and different Machine Learning models were utilized in the analyzed publications and the use of BD-based techniques enabled us to extract useful correlations and gain useful insights from large volumes of data.

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Section: Supporting Military Operationsmentioning

confidence: 99%

Section: Subcategory Specific Applicationmentioning

confidence: 99%

Applications and Technologies of Big Data in the Aerospace Domain

Adamopoulou

Daskalakis

2023

Electronics

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“…Because of these features, the department of defense is using this methodology to correct, fast and safety decisions on the basis of available data by analyzing it. [12]. Peter Triantafillou, et al developed new models, algorithms, and compositions that learn from the system's responses to particular analyst queries.…”

Section: Literature Reviewmentioning

confidence: 99%

Examination of Big Dataset using LEOS, JOSE, SVM on Map Reduce

2019

IJITEE

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Data analytics (DA) is the job of reviewing datasets in order to frame conclusions about the information they have, increasingly using specialized systems and software. As with the emergence of Big Data, data analytics was needed. The problems that we are considering are going to be in a fraud detection application. Where we'll considering major aspects such application-independent format(XML/JSON) for the clusterization process based on the no label classification algorithm where we will focusing on the clusters to enhance the oversampling process and utilize the merits of parallel computing to speed up our system. We aim to use MapReduce functionality in our application and deploy it on Amazon AWS. Datasets gathered for studies often comprise millions of records and can carry hard-to-detect concealed pitfalls. In this paper, we are working on two datasets. The first one is a medical dataset and the second one is a customer dataset. Big Data Analytics is the suggested solution in this day and age, with growing demands for analyzing huge information sets and performing the required processing on complicated data structures. The problem faced at the moment is mainly, how to store and analyze the large amount of data which is generated from heterogeneous sources like social media and what to use to make data fast accessible as well as in pocket budget. To resolve all problems Map-Reduce framework is useful-by offering an integrated technique towards machine learning, it speeds up processing. In this, we will explore the LEOS algorithm, SVM, MapReduce and JOSE algorithm, their requirements, their benefits, their disadvantages, difficulties, and their corresponding solutions.

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Big Data Analytics for Market Prediction via Consumer Insight

Soni

Sharma

2021

Big Data Analytics in Cognitive Social Media and Literary Texts

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Using Big Data Analytics to Create a Predictive Model for Joint Strike Fighter

Cited by 5 publications

References 0 publications

Applications and Technologies of Big Data in the Aerospace Domain

Applications and Technologies of Big Data in the Aerospace Domain

Examination of Big Dataset using LEOS, JOSE, SVM on Map Reduce

Big Data Analytics for Market Prediction via Consumer Insight

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