Sökning: "Återkopplande Neurala Nätverk"

Hittade 3 uppsatser innehållade orden Återkopplande Neurala Nätverk.

1. 1. Maximizing Recommendation System Accuracy In E-Commerce for Clothing And Accessories for Children

   Master-uppsats, KTH/Matematik (Avd.)

   Författare :Niklas Renström; [2022]
   Nyckelord :Recommendation System; Session Based; E-Commerce; Clothes; Children s Fashion; Machine Learning; RNN; LSTM; GRU; STAMP; Rekommendationssystem; Sessionsbaserad; E-handel; Kläder; Barnmode; Maskininlärning; Återkopplande Neurala Nätverk;

   Sammanfattning : The industry of electronic commerce (e-commerce) constitutes a great part of the yearly retail consumption in Sweden. Looking at recent years, it has been seen that a rapidly growing sector within the mentioned field is the clothing industry for clothes and accessories for children and newborns. LÄS MER

3. 2. PC Regression, Vector Autoregression, and Recurrent Neural Networks: How do they compare when predicting stock index returns for building efficient portfolios?

   Master-uppsats, KTH/Optimeringslära och systemteori

   Författare :David Hallberg; Erik Renström; [2019]
   Nyckelord :PC Regression; Vektorautoregression; och Återkopplande Neurala Nätverk: En jämförelse mellan deras förmåga att prognostisera aktieindexavkastning för att konstruera effektiva portföljer; Huvudkomponentregression; vektorautoregression; LSTM; återkopplande neurala nätverk; portföljteori; portföljoptimering; maskininlärning; makroekonomi; finans; aktieavkastning; aktieindex;

   Sammanfattning : This thesis examines the statistical and economic performance of modeling and predicting equity index returns by application of various statistical models on a set of macroeconomic and financial variables. By combining linear principal component regression, vector autoregressive models, and LSTM neural networks, the authors find that while a majority of the models display high statistical significance, virtually none of them successfully outperform classic portfolio theory on efficient markets in terms of risk-adjusted returns. LÄS MER

4. 3. Tracking a ball during bounce and roll using recurrent neural networks

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

   Författare :Felicia Rosell; [2018]
   Nyckelord :machine learning; ML; recurrent neural networks; RNN; deep learning; tracking; golf; bounce; synthetic data; maskininlärning; ML; recurrent neural networks; RNN; djupinlärning; följning; golf; studs; syntetiskt data;

   Sammanfattning : In many types of sports, on-screen graphics such as an reconstructed ball trajectory, can be displayed for spectators or players in order to increase understanding. One sub-problem of trajectory reconstruction is tracking of ball positions, which is a difficult problem due to the fast and often complex ball movement. LÄS MER