Essays about: "anomalitetsdetektering"
Showing result 1 - 5 of 8 essays containing the word anomalitetsdetektering.
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1. Detecting Faults in Telecom Software Using Diffusion Models : A proof of concept study for the application of diffusion models on Telecom data
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : This thesis focuses on software fault detection in the telecom industry, which is crucial for companies like Ericsson to ensure stable and reliable software. Given the importance of software performance to companies that rely on it, automatically detecting faulty behavior in test or operational environments is challenging. READ MORE
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2. Anomaly Detection in Categorical Data with Interpretable Machine Learning : A random forest approach to classify imbalanced data
University essay from Linköpings universitet/Statistik och maskininlärningAbstract : Metadata refers to "data about data", which contains information needed to understand theprocess of data collection. In this thesis, we investigate if metadata features can be usedto detect broken data and how a tree-based interpretable machine learning algorithm canbe used for an effective classification. The goal of this thesis is two-fold. READ MORE
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3. Anomaly Detection in Unstructured Time Series Datausing an LSTM Autoencoder
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : An exploration of anomaly detection. Much work has been done on the topic of anomalyd etection, but what seems to be lacking is a dive into anomaly detection of unstructuredand unlabeled data. This thesis aims to determine the efctiveness of combining recurrentneural networks with autoencoder structures for sequential anomaly detection. READ MORE
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4. Unsupervised Anomaly Detection on Multi-Process Event Time Series
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Establishing whether the observed data are anomalous or not is an important task that has been widely investigated in literature, and it becomes an even more complex problem if combined with high dimensional representations and multiple sources independently generating the patterns to be analyzed. The work presented in this master thesis employs a data-driven pipeline for the definition of a recurrent auto-encoder architecture to analyze, in an unsupervised fashion, high-dimensional event time-series generated by multiple and variable processes interacting with a system. READ MORE
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5. Detection and Classification of Anomalies in Road Traffic using Spark Streaming
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Road traffic control has been around for a long time to guarantee the safety of vehicles and pedestrians. However, anomalies such as accidents or natural disasters cannot be avoided. Therefore, it is important to be prepared as soon as possible to prevent a higher number of human losses. READ MORE
