Sökning: "MAPE"

Visar resultat 1 - 5 av 65 uppsatser innehållade ordet MAPE.

1. 1. Using artificial intelligence to improvetime estimation for project management

   Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Signaler och system

   Författare :Marcus Bonnedahl; [2024]
   Nyckelord :time estimation; ai; machine learning; project management;

   Sammanfattning : Time estimation is an important aspect in project management. Failure to make accurateestimates can lead to large consequences. Despite this, humans tend to make fairly inaccurateestimates when tasked to, often underestimating the time something will take substantially. LÄS MER

3. 2. On modelling OMXS30 stocks - comparison between ARMA models and neural networks

   Master-uppsats, Uppsala universitet/Matematiska institutionen

   Författare :Irina Zarankina; [2023]
   Nyckelord :ARMA; ARIMA; LSTM; time series; statistics;

   Sammanfattning : This thesis compares the results of the performance of the statistical Autoregressive integrated moving average (ARIMA) model and the neural network Long short-term model (LSTM) on a data set, which represents a market index. Both models are used to predict monthly, daily, and minute close prices of the OMX Stockholm 30 Index. LÄS MER

4. 3. COMPARATIVE ANALYSIS OF MACHINE LEARNING LOAD FORECASTING TECHNIQUES

   Magister-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

   Författare :Humphry Takang Bate; [2023]
   Nyckelord :;

   Sammanfattning : Load forecasting plays a critical role in energy management, and power systems, enabling efficient resource allocation, improved grid stability, and effective energy planning and distribution. Without accurate very short term load forecasting, utility management companies face uncertain load patterns, unrealistic prices, and poor infrastructure planning. LÄS MER

5. 4. Dark Matter signals at the Large Hadron Collider with Deep Learning

   Kandidat-uppsats, Uppsala universitet/Institutionen för informationsteknologi

   Författare :Max Andersson; Edward Glöckner; Carl Löfkvist; [2023]
   Nyckelord :Machine Learning; Dark Matter; Classification; Regression; Particle Physics; Supersymmetry; LHC; CERN;

   Sammanfattning : While holding a firm position in popular culture and science fiction, Dark Matter (DM) is nonetheless a highly relevant topic at the forefront of modern particle physics. We study the applicability of characterizing DM particle candidates SUSY neutralino and sneutrino using Deep Learning (DL) methods. LÄS MER

7. 5. Forecasting Monthly Swedish Air Traveler Volumes

   Kandidat-uppsats, Uppsala universitet/Statistiska institutionen

   Författare :Mark Becker; Peter Jarvis; [2023]
   Nyckelord :Forecasting; SARIMA; Neural network autoregression; Exponential smoothing; the Prophet model; Random Walk; MAE; MAPE; RMSE;

   Sammanfattning : In this paper we conduct an out-of-sample forecasting exercise for monthly Swedish air traveler volumes. The models considered are multiplicative seasonal ARIMA, Neural network autoregression, Exponential smoothing, the Prophet model and a Random Walk as a benchmark model. LÄS MER