Essays about: "RMSE"
Showing result 21 - 25 of 234 essays containing the word RMSE.
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21. Data-driven Interpolation Methods Applied to Antenna System Responses : Implementation of and Benchmarking
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : With the advances in the telecommunications industry, there is a need to solve the in-band full-duplex (IBFD) problem for antenna systems. One premise for solving the IBFD problem is to have strong isolation between transmitter and receiver antennas in an antenna system. READ MORE
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22. Enhancing House Rental Price Prediction Models for the Swedish Market : Exploring External features, Prediction intervals and Uncertainty Management in Predicting House Rental Prices
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Exakt förutsägelse av hyrespriserna för hus är ett avgörande problem i verkligheten fastighetsdomän, vilket underlättar informerat beslutsfattande för både hyresgäster och hyresvärdar. Denna studie presenterar en omfattande utforskning av olika maskininlärningstekniker som tillämpas på en mångsidig datauppsättning av husfunktioner, med det övergripande målet att avslöja den mest effektiva algoritmen för förutsäga hyrespriser. READ MORE
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23. Detecting Metro Service Disruptions and Predicting their Spillover Effects throughout the Network using GTFS and Large-Scale Vehicle Location Data
University essay from KTH/TransportplaneringAbstract : One of the top factors that influence commuters’ satisfaction level with public transport is the punctuality of the service. Commuters rely on public transport to get them from their origin to destination on time and any form of delay will incur additional cost to both the commuters as well as the public transport operators. READ MORE
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24. Forecasting copper price using VAR and the XGBoost model: an experiment with a relatively small dataset
University essay from Lunds universitet/Nationalekonomiska institutionen; Lunds universitet/Statistiska institutionenAbstract : Given the importance of copper prices to investors, governments, and policymakers, this paper investigates short-term price predictability using VAR and XGBoost models. All models are trained with historical data from November 2021 to December 2022 and using MSE, RMSE and MAE for evaluating the model performance. READ MORE
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25. A Mixed Time-Series & Machine Learning Approach for Price Forecasting in the Swedish Ancillary Market
University essay from Lunds universitet/Nationalekonomiska institutionen; Lunds universitet/Statistiska institutionenAbstract : This study aims to forecast the Swedish FCR-D Down A2 market prices through a hybrid model combining a volatility model and a machine learning approach, and compares its performance with a standalone machine learning model. We further examine the impact of different lag orders (1-Hr vs. 24-Hr) on volatility estimates and forecast performance. READ MORE