Essays about: "LSTM AutoEncoder"

Showing result 6 - 10 of 29 essays containing the words LSTM AutoEncoder.

1. 6. Cooperative security log analysis using machine learning : Analyzing different approaches to log featurization and classification

   University essay from Linköpings universitet/Databas och informationsteknik

   Author : Fredrik Malmfors; [2022]
   Keywords : Machine learning; word embeddings; deep learning; LSTM; CNN; auto encoder; NLP; natural language processing; intrusion detection; log analysis; logs; log classification; anomaly detection; supervised learning; unsupervised learning;

   Abstract : This thesis evaluates the performance of different machine learning approaches to log classification based on a dataset derived from simulating intrusive behavior towards an enterprise web application. The first experiment consists of performing attacks towards the web app in correlation with the logs to create a labeled dataset. READ MORE

3. 7. Sensor modelling for anomaly detection in time series data

   University essay from Linköpings universitet/Statistik och maskininlärning

   Author : ZAHRA JALIL POUR; [2022]
   Keywords : anomaly detection; LSTM; Autoencoder; multivariate time series data;

   Abstract : Mechanical devices in industriy are equipped with numerous sensors to capture thehealth state of the machines. The reliability of the machine’s health system depends on thequality of sensor data. In order to predict the health state of sensors, abnormal behaviourof sensors must be detected to avoid unnecessary cost. READ MORE

4. 8. Federated Learning for Market Surveillance

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

   Author : Philip Song; [2022]
   Keywords : Federated Learning; Machine Learning; Market Surveillance; Anomaly Detection; LSTMAutoencoder; Federated Learning; Maskininlärning; Marknadsövervakning; Anomaliupptäckande; LSTMAutoencoder;

   Abstract : The increasing complexity of trading strategies, when combined with machine learning models, forces market surveillance corporations to develop increasingly sophisticated methods for recognizing potential misuse. One strategy is to employ traders’ weapons against themselves, namely machine learning. READ MORE

5. 9. Training Autoencoders for feature extraction of EEG signals for motor imagery

   University essay from Mälardalens högskola/Akademin för innovation, design och teknik

   Author : Casper Wahl; [2021]
   Keywords : ;

   Abstract : Electroencephalography (EEG) is a common technique used to read brain activity from an individual, and can be used for a wide range of applications, one example is during the rehab process of stroke victims. Loss of motor function is a common side effect of strokes, and the EEG signals can show if sufficient activation of the part of the brain related to the motor function that the patient is training has been achieved. READ MORE

6. 10. A deep learning based anomaly detection pipeline for battery fleets

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

   Author : Nabakumar Singh Khongbantabam; [2021]
   Keywords : 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.;

   Abstract : 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. READ MORE