Essays about: "multivariate time-series data"

Showing result 1 - 5 of 60 essays containing the words multivariate time-series data.

  1. 1. Smart Alarm- On the performance characteristics of linear, multi-linear and non-linear tensor models for alarm prediction in multi-sensor data.

    University essay from Högskolan i Halmstad/Akademin för informationsteknologi

    Author : Chandraprakash Sahu; Ahamed Buhari; [2022]
    Keywords : Machine Learning; Tensor Regression; Deep Learning; Multivariate Time Series;

    Abstract : Information and modern computing technology advancements have led to a rise in the importance of maintenance, particularly in areas where a single components failure could have a significant impact on the overall systems performance. Numerous industries, including Alfa Laval, are operating on conditional-based systems that provide warnings only when a machine fails. READ MORE

  2. 2. Multivariate Time Series Prediction for DevOps : A first Step to Fault Prediction of the CI Infrastructure

    University essay from Linköpings universitet/Statistik och maskininlärning

    Author : Yiran Wang; [2022]
    Keywords : VAR; LSTM; BiLSTM; time series; CI; DevOps;

    Abstract : The continuous integration infrastructure (CI servers) is commonly used as a shared test environment due to the need for collaborative and distributive development for the software products under growing scale and complexity in recent years. To ensure the stability of the CI servers, with the help of the constantly recorded measurement data of the servers, fault prediction is of great interest to software development companies. READ MORE

  3. 3. Time Dependencies Between Equity Options Implied Volatility Surfaces and Stock Loans, A Forecast Analysis with Recurrent Neural Networks and Multivariate Time Series

    University essay from KTH/Matematik (Avd.)

    Author : Simon Wahlberg; [2022]
    Keywords : RNN; LSTM; GRU; vector autoregression; implied volatility surface; stock loan; equity options; multivariate time-series analysis; financial mathematics.; Rekursiva neurala nätverk; LSTM; GRU; VAR; implicerade volatilitetsytor; aktielån; aktieoptioner; multidimensionell tidsserieanalys; finansiell matematik.;

    Abstract : Synthetic short positions constructed by equity options and stock loan short sells are linked by arbitrage. This thesis analyses the link by considering the implied volatility surface (IVS) at 80%, 100%, and 120% moneyness, and stock loan variables such as benchmark rate (rt), utilization, short interest, and transaction trends to inspect time-dependent structures between the two assets. READ MORE

  4. 4. Peacekeepers Protecting Civilians, Under the Threat of Violence : A quantitative cross-national analysis on how the risk of violence towards peacekeepers affects their ability to protect civilians

    University essay from Uppsala universitet/Institutionen för freds- och konfliktforskning

    Author : Emil Lewenhaupt; [2022]
    Keywords : peacekeeping; one-sided violence; risk of violence against peacekeepers; UN;

    Abstract : While peacekeeping operations have been researched for decades, due to a lack of data there are still many aspects of peacekeeping that remain unexplored. However, with the introduction of the Peacemakers at Risk dataset a wide array of dynamics and relationships can now be researched. READ MORE

  5. 5. AUGMENTATION AND CLASSIFICATION OF TIME SERIES FOR FINDING ACL INJURIES

    University essay from Umeå universitet/Institutionen för datavetenskap

    Author : Marie-Louise Johansson; [2022]
    Keywords : computer science; machine learning; motion analysis; reconstructed ACL; anterior cruciate ligament; time series forest; dynamic time wapring; ACL; multivariate time series clasification; MTSC; time series classification; TSC; euclidean barycentric average; euclidean barycentric averaging; autmentation of time series; augmentation of multivariate time series; data augmentation; augmentation;

    Abstract : This thesis addresses the problem where we want to apply machine learning over a small data set of multivariate time series. A challenge when classifying data is when the data set is small and overfitting is at risk. Augmentation of small data sets might avoid overfitting. READ MORE