Essays about: "Collective Anomaly"

Showing result 1 - 5 of 6 essays containing the words Collective Anomaly.

  1. 1. Unsupervised Anomaly Detection for Humidity Sensor Data

    University essay from Lunds universitet/Statistiska institutionen; Lunds universitet/Nationalekonomiska institutionen

    Author : Pinyapat Manasboonpermpool; Dirk Willeboord Baars; [2022]
    Keywords : LSTM; Auto-Encoder; Anomaly Detection; Time series; Deep Learning; Business and Economics;

    Abstract : Detecting anomalies in loT sensor devices for humidity is crucial for the maintenance and safety of households and buildings. An Auto-Encoder (AE) can detect anomalies in sensor data. However, the reality is that most sensor data is unlabelled, while it is recommended to use labelled data when training the model for anomaly detection with AE. READ MORE

  3. 2. Unsupervised Anomaly Detection on Time Series Data: An Implementation on Electricity Consumption Series

    University essay from KTH/Matematisk statistik

    Author : Amelia Lindroth Henriksson; [2021]
    Keywords : Unsupervised learning; machine learning; anomaly detection; time series; electricity consumption; synthetic anomalies; DBSCAN; LOF; iForest; OC-SVM; Oövervakad inlärning; maskininlärning; anomalidetektion; tidsserier; elförbrukning; syntetiska anomalier; DBSCAN; LOF; iForest; OC-SVM;

    Abstract : Digitization of the energy industry, introduction of smart grids and increasing regulation of electricity consumption metering have resulted in vast amounts of electricity data. This data presents a unique opportunity to understand the electricity usage and to make it more efficient, reducing electricity consumption and carbon emissions. READ MORE

  4. 3. Unsuperised Anomaly Detection : Methods and Application on Solvency 2 Technical Provisions

    University essay from Umeå universitet/Institutionen för matematik och matematisk statistik

    Author : Richard Olofsson; [2020]
    Keywords : ;

    Abstract : This thesis work examines anomaly detection methods on large data sets related to insurance funds. Starting from requirements of low time complexity, ease of implementation and thorough definitions of contextual- and collective anomalies, different modelling frameworks are examined. READ MORE

  5. 4. Anomaly detection for non-recurring traffic congestions using Long short-term memory networks (LSTMs)

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : John Svanberg; [2018]
    Keywords : ML; machine learning; neural networks; recurrent neural networks; NN; RNN; LSTM; long short-term memory networks; anomaly detection; public transport; big data; data analysis;

    Abstract : In this master thesis, we implement a two-step anomaly detection mechanism for non-recurrent traffic congestions with data collected from public transport buses in Stockholm. We investigate the use of machine learning to model time series data with LSTMs and evaluate the results with a baseline prediction model. READ MORE

  6. 5. PRAAG Algorithm in Anomaly Detection

    University essay from KTH/Skolan för elektro- och systemteknik (EES)

    Author : Dongyang Zhang; [2016]
    Keywords : Anomaly detection; Collective Anomaly; Algorithm; Data Mining 1; Detektion av avvikelser; kollektiv avvikelse; algorithm; datautvinning;

    Abstract : Anomaly detection has been one of the most important applications of datamining, widely applied in industries like financial, medical,telecommunication, even manufacturing. In many scenarios, data are in theform of streaming in a large amount, so it is preferred to analyze the datawithout storing all of them. READ MORE