Sökning: "syntetiska anomalier"

Hittade 5 uppsatser innehållade orden syntetiska anomalier.

1. 1. Unsupervised Machine Learning Based Anomaly Detection in Stockholm Road Traffic

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

   Författare :Vilma Hellström; [2023]
   Nyckelord :Anomaly detection; DBSCAN; LSTM; Machine learning; Synthetic anomalies; Unsupervised learning; Anomalidetektering; DBSCAN; LSTM; maskininlärning; syntetiska anomalier; oövervakad inlärning;

   Sammanfattning : This thesis is a study of anomaly detection in vehicle traffic data in central Stockholm. Anomaly detection is an important tool in the analysis of traffic data for improved urban planing. Two unsupervised machine learning models are used, the DBSCAN clustering model and the LSTM deep learning neural network. LÄS MER

3. 2. A Review of Anomaly Detection Techniques forHeterogeneous Datasets

   Master-uppsats, KTH/Optimeringslära och systemteori

   Författare :Shirwan Piroti; [2021]
   Nyckelord :Anomaly Detection; Heterogeneous; GAN; BiGAN; Autoencoder; Random Forest; Isolation Forest; Anomalidetektering; Heterogen; GAN; BiGAN; Autoencoder; Random Forest; Isolation Forest;

   Sammanfattning : Anomaly detection is a field of study that is closely associated with machine learning and it is the process of finding irregularities in datasets. Developing and maintaining multiple machine learning models for anomaly detection takes time and can be an expensive task. One proposed solution is to combine all datasets and create a single model. LÄS MER

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

   Master-uppsats, KTH/Matematisk statistik

   Författare :Amelia Lindroth Henriksson; [2021]
   Nyckelord :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;

   Sammanfattning : 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. LÄS MER

5. 4. Outlier detection for overnight index swaps

   Master-uppsats, Umeå universitet/Institutionen för matematik och matematisk statistik

   Författare :Jonny Kuo; [2020]
   Nyckelord :;

   Sammanfattning : I examensarbetet undersöks metoder för anomalidetektion i tidsserie data. Givet data för overnight index swaps (SEK), så har syntetiskt data skapats med olika ty-per av anomalier. LÄS MER

7. 5. Unsupervised real-time anomaly detection on streaming data for large-scale application deployments

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

   Författare :Carl Jernbäcker; [2019]
   Nyckelord :;

   Sammanfattning : Anomaly detection is the classification of data points that do not adhere to the familiar pattern; in previous studies there existed a need for extensive human interactions with either labelling or sorting normal and abnormal data from one another. In this thesis, we want to go one step further and apply machine learning techniques on time-series data in order to have a deeper understanding of the properties of a given data point without any sorting and labelling. LÄS MER