Essays about: "nätverk med långt korttidsminne"

Showing result 1 - 5 of 7 essays containing the words nätverk med långt korttidsminne.

1. 1. Supervised Algorithm for Predictive Maintenance

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

   Author : Haida Lu; [2023]
   Keywords : Long short-term memory; Predictive maintenance; Remaining useful life; Embedded Artificial Intelligence; Långt korttidsminne; förebyggande underhåll; återstående livslängd; inbyggd artificiell intelligens;

   Abstract : Predictive maintenance plays a crucial role in preventing unexpected equipment failures and maintaining assets in good operating conditions in various systems. One such scenario where predictive maintenance has been widely used is in battery management systems for electronic vehicles based on lithium batteries, where the risk of failure can be reduced by predicting the remaining useful life of the lithium battery. READ MORE

3. 2. Convolutional-LSTM for IGBTs Prognostics and Age Monitoring : Designing a neural network for predicting aging precursors in power devices

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

   Author : Matteo Santoro; [2023]
   Keywords : Neural Networks; Igbt; Prognostics; Age Monitoring; Neurala Nätverk; Igbt; Prognostik; Övervakning av Ålder;

   Abstract : In recent years, extensive research efforts have been dedicated to the field of prognostics and age-related degradation, with major focus on higher complexity devices. However, relatively little attention has been given to power devices, such as Insulated Bipolar Gate Transistors (IGBTs), despite their critical role in high power electronic applications. READ MORE

4. 3. Development of a Software Reliability Prediction Method for Onboard European Train Control System

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

   Author : Guillaume Pierre Longrais; [2021]
   Keywords : Machine Learning; Software Reliability Growth Prediction; Linear Regression; Artificial Neural Network; Multi-Layer Perceptron; Imperialist Competitive Algorithm; Long Short-Term Memory Network; Convolutional Neural Network; Maskininlärning; förutsägelse av tillväxten av programvarans tillförlitlighet; linjär regression; artificiellt neuralt nätverk; flerskikts-perceptron; imperialistisk konkurrensalgoritm; nätverk med långt korttidsminne; konvolutionellt neuralt nätverk;

   Abstract : Software prediction is a complex area as there are no accurate models to represent reliability throughout the use of software, unlike hardware reliability. In the context of the software reliability of on-board train systems, ensuring good software reliability over time is all the more critical given the current density of rail traffic and the risk of accidents resulting from a software malfunction. READ MORE

5. 4. Predictive vertical CPU autoscaling in Kubernetes based on time-series forecasting with Holt-Winters exponential smoothing and long short-term memory

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

   Author : Thomas Wang; [2021]
   Keywords : Kubernetes; Docker; Container; Cloud Native; Cloud Computing; Resource Provisioning; Autoscaling; Predictive scaling; CPU Usage; Seasonality; Exponential Smoothing; Long short-term memory; Time-series Analysis; Kubernetes; Docker; Container; Cloud Native; Cloud Computing; Resursförsörjning; Autoskalning; prediktiv skalning; CPU Användning; Säsongsmässighet; Exponentiell utjämning; långt korttidsminne; tidsserieanalys;

   Abstract : Private and public clouds require users to specify requests for resources such as CPU and memory (RAM) to be provisioned for their applications. The values of these requests do not necessarily relate to the application’s run-time requirements, but only help the cloud infrastructure resource manager to map requested virtual resources to physical resources. READ MORE

6. 5. Pulse Repetition Interval Modulation Classification using Machine Learning

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

   Author : Eric Norgren; [2019]
   Keywords : machine learning; radar; radar pulses; radar signals; pulseradar; pulse repetition interval; modulation; classification; LSTM; long short term memory; feature extraction; saab; ai; artifical intelligence; radar warning receiver; rwr; neural network; maskininlärning; radar; radarpulser; radar signaler; pulsradar; pulsrepetitionsintervall; modulationstyp; modulering; klassificering; LSTM; long short term memory; särdrag; saab; ai; artificiell intelligens; radarvarnare; rwr; neuralt nätverk;

   Abstract : Radar signals are used for estimating location, speed and direction of an object. Some radars emit pulses, while others emit a continuous wave. Both types of radars emit signals according to some pattern; a pulse radar, for example, emits pulses with a specific time interval between pulses. READ MORE