Sökning: "Isolation nearest neighbor"

Hittade 2 uppsatser innehållade orden Isolation nearest neighbor.

  1. 1. A deep learning based anomaly detection pipeline for battery fleets

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Nabakumar Singh Khongbantabam; [2021]
    Nyckelord :Forklift batteries; Battery sensors; Data pipeline; Predictive maintenance; Anomaly detection; Deep learning; Battery failure prediction; Time-series; Variational autoencoder; Long short-term memory; LSTM; Gated recurrent unit; GRU; Isolation nearest neighbor; iNNE; Isolation forest; iForest; kth nearest neighbor; kNN.; Gaffeltruckbatterier; Batterisensorer; Datapipeline; Prediktivt underhåll; Avvikelsedetektering; Deep learning; Batterifelsprediktion; Tidsserier; Variationsautokodare; Långt korttidsminne; LSTM; Gated recurrent unit; GRU; Isolation närmaste granne; iNNE; Isolation skog; iForest; kth närmaste granne; kNN.;

    Sammanfattning : This thesis proposes a deep learning anomaly detection pipeline to detect possible anomalies during the operation of a fleet of batteries and presents its development and evaluation. The pipeline employs sensors that connect to each battery in the fleet to remotely collect real-time measurements of their operating characteristics, such as voltage, current, and temperature. LÄS MER

  3. 2. Fault Isolation By Manifold Learning

    Uppsats för yrkesexamina på avancerad nivå, Fordonssystem

    Författare :Mårten Thurén; [1985]
    Nyckelord :manifold; pca; lda; laplacian eigenmaps; fault isolation; fault diagnosis;

    Sammanfattning : This thesis investigates the possibility of improving black box fault diagnosis by a process called manifold learning, which simply stated is a way of finding patterns in recorded sensor data. The idea is that there is more information in the data than is exploited when using simple classification algorithms such as k-Nearest Neighbor and Support Vector Machines, and that this additional information can be found by using manifold learning methods. LÄS MER