Location
https://ccse.kennesaw.edu/computing-showcase/cday-programs/fall23program.php
Document Type
Event
Start Date
30-11-2023 4:00 PM
Description
The widespread adoption of global positioning technology has led to an increase in products featuring GPS functionality. These devices gather large amounts of location data. However, inherent inaccuracies in GPS data collection are unavoidable. To address these challenges, we shift our focus to identifying the closest points in a location. This requires gathering data to measure distances between a point and all others, and keeping a record of the nearest points. In this project, the Naive Bayes,SVM, k-means, and KNN algorithms are employed to determine the nearest points.
Included in
eGR-470 Optimizing the Search in Location Using SVM, Naive Bayes, K-Means and KNN
https://ccse.kennesaw.edu/computing-showcase/cday-programs/fall23program.php
The widespread adoption of global positioning technology has led to an increase in products featuring GPS functionality. These devices gather large amounts of location data. However, inherent inaccuracies in GPS data collection are unavoidable. To address these challenges, we shift our focus to identifying the closest points in a location. This requires gathering data to measure distances between a point and all others, and keeping a record of the nearest points. In this project, the Naive Bayes,SVM, k-means, and KNN algorithms are employed to determine the nearest points.