GitHub / zekeriyyaa / Anomaly-Detection-Based-on-Clustering-of-Mobile-Robot-Data
We proposed a new approach to detect anomalies of mobile robot data. We investigate each data seperately with two clustering method hierarchical and k-means. There are two sub-method that we used for produce an anomaly score. Then, we merge these two score and produce merged anomaly score as a result.
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PURL: pkg:github/zekeriyyaa/Anomaly-Detection-Based-on-Clustering-of-Mobile-Robot-Data
Stars: 3
Forks: 1
Open issues: 0
License: None
Language: Python
Size: 2.16 MB
Dependencies parsed at: Pending
Created at: over 3 years ago
Updated at: almost 2 years ago
Pushed at: over 3 years ago
Last synced at: 4 months ago
Topics: agv, anomaly, clustering, currency, dtw, dynamic-time-warping, feature-extraction, hierarchical-clustering, k-means-clustering, mobile-robots, normalization, python, robotics, time-series-analysis, time-series-data, vibration