Essays about: "Tidsseriedata"

Showing result 21 - 25 of 60 essays containing the word Tidsseriedata.

  1. 21. 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

  3. 22. Multivariate Time Series Data Generation using Generative Adversarial Networks : Generating Realistic Sensor Time Series Data of Vehicles with an Abnormal Behaviour using TimeGAN

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

    Author : Sofia Nord; [2021]
    Keywords : Time Series Data Generation; Generative Adversarial Network; Deep Neural Network; Data Augmentation; Synthetic Data Generation; Generering av Tidsseriedata; Generativa Motstridande Nätverk; Djupa Neurala Nätverk; Dataökning; Syntetisk Datagenerering;

    Abstract : Large datasets are a crucial requirement to achieve high performance, accuracy, and generalisation for any machine learning task, such as prediction or anomaly detection, However, it is not uncommon for datasets to be small or imbalanced since gathering data can be difficult, time-consuming, and expensive. In the task of collecting vehicle sensor time series data, in particular when the vehicle has an abnormal behaviour, these struggles are present and may hinder the automotive industry in its development. READ MORE

  4. 23. Simulation and time-series analysis for Autonomous Emergency Braking systems

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

    Author : Zhiying Xu; [2021]
    Keywords : Autonomous Driving AD ; CARLA; Autonomous Emergency Braking AEB ; Deep Learning; Time-series analysis; Autonom körning; CARLA; Autonomt nödsystem; Djup lärning; Tidsföljder;

    Abstract : One central challenge for Autonomous Driving (AD) systems is ensuring functional safety. This is affected by all parts of vehicle automation systems: environment perception, decision making, and actuation. READ MORE

  5. 24. Transfer learning techniques in time series analysis

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

    Author : Robinson Sablons de Gélis; [2021]
    Keywords : Deep learning; Time series; Transfer learning; Self-supervised learning; Domain adaptation; Djupinlärning; tidsserier; överföringsinlärning; självövervakad inlärning; domänanpassning;

    Abstract : Deep learning works best with vast andd well-distributed data collections. However, collecting and annotating large data sets can be very time-consuming and expensive. Moreover, deep learning is specific to domain knowledge, even with data and computation. E. READ MORE

  6. 25. Neural Ordinary Differential Equations for Anomaly Detection

    University essay from KTH/Matematisk statistik

    Author : Jón Hlöðver Friðriksson; Erik Ågren; [2021]
    Keywords : Anomaly detection; Neural ordinary differential equations; Statistical modelling; Autoregression; Variational autoencoder; Multivariate time series; Anomalidetektion; Neurala ordinära differentialekvationer; Statistisk modellering; Autoregression; Variational autoencoder; Multivariat tidsserie;

    Abstract : Today, a large amount of time series data is being produced from a variety of different devices such as smart speakers, cell phones and vehicles. This data can be used to make inferences and predictions. Neural network based methods are among one of the most popular ways to model time series data. READ MORE