File:USING APACHE SPARK TO SPEED ANALYSIS OF ADS-B AIRCRAFT-TRACKING DATA TECHNIQUES (IA usingapachespark1094559630).pdf
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USING APACHE SPARK TO SPEED ANALYSIS OF ADS-B AIRCRAFT-TRACKING DATA TECHNIQUES
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| Author |
Zhou, Jim Z. |
| Title |
USING APACHE SPARK TO SPEED ANALYSIS OF ADS-B AIRCRAFT-TRACKING DATA TECHNIQUES |
| Publisher |
Monterey, CA; Naval Postgraduate School |
| Description |
The U.S. Navy is exploring the feasibility of using a big-data platform and machine-learning algorithms to analyze combat-identification data. Combat identification involves a large number of remote sensors that report back data for aggregation and analysis. In this thesis, we used a sample of ADS-B aircraft-tracking data to test big-data methods for machine-learning methods developed previously. We showed large speed improvements in the analysis setup over the previous single-processor methods, and a lesser speed improvement for machine-learning based anomaly analysis. Subjects: big data; machine learning; Apache Spark; ADS-B |
| Language | English |
| Publication date | June 2018 |
| Current location |
IA Collections: navalpostgraduateschoollibrary; fedlink |
| Accession number |
usingapachespark1094559630 |
| Source | |
| Permission (Reusing this file) |
Copyright is reserved by the copyright owner. |
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| current | 19:42, 25 July 2020 |  | 1,275 × 1,650, 64 pages (548 KB) | Fæ (talk | contribs) | FEDLINK - United States Federal Collection usingapachespark1094559630 (User talk:Fæ/IA books#Fork8) (batch 1993-2020 #31605) |
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