Sökning: "återkopplade neurala nätverk"

Hittade 3 uppsatser innehållade orden återkopplade neurala nätverk.

  1. 1. FLEX: Force Linear to Exponential : Improving Time Series Forecasting Models For Hydrological Level Using A Scalable Ensemble Machine Learning Approach

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Koen van den Brink; [2022]
    Nyckelord :machine learning; time-series forecasting; water level forecasting; time-series transformers; recurrent neural networks; maskininlärning; tidsserieprognoser; vattenståndsprognoser; tidsserietransformatorer; återkopplade neurala nätverk;

    Sammanfattning : Time-series forecasting is an area of machine learning that can be applied to many real-life problems. It is used in areas such as water level forecasting, which aims to help people evacuate on time for floods. LÄS MER

  3. 2. Role of Context in Episodic Memory : A Bayesian-Hebbian Neural Network Model of Episodic Recall

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Rohan Raj; [2022]
    Nyckelord :episodic memory; long-term memory; Bayesian Confidence Propagation Neural Network; synaptic plasticity; plasticity modulation; computational neuroscience;

    Sammanfattning : Episodic memory forms a fundamental aspect of human memory that accounts for the storage of events as well as the spatio-temporal relations between events during a lifetime. These spatio-temporal relations in which episodes are embedded can be understood as their contexts. Contexts play a crucial role in episodic memory retrieval. LÄS MER

  4. 3. Change Point Detection in Sequential Sensor Data using Recurrent Neural Networks

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Veeresh Elango; [2018]
    Nyckelord :;

    Sammanfattning : Change-point detection is the problem of recognizing the abrupt variations in sequential data. This covers a wide range of real world problems within medical, meteorology and automotive industry, and has been actively addressed in the community of statistics and data mining. LÄS MER