Dynamic mean absolute error as new measure for assessing forecasting errors
Energy Conversion and Management, 2018 Accurate wind power forecast is essential for grid integration, system planning, and electricity trading in certain electricity markets. Therefore, analyzing prediction errors is a critical task that allows a comparison of prediction models and the selection of the most suitable model.
Laura Frías-Paredes +2 more
exaly +4 more sources
Optimizing LSTM Models for EUR/USD Prediction in the context of reducing energy consumption: An Analysis of Mean Squared Error, Mean Absolute Error and R-Squared [PDF]
E3S Web of Conferences, 2023 The purpose of this study was to develop and evaluate a Long Short-Term Memory (LSTM) model for Forex prediction. The data used was reprocessed and the LSTM model was developed and trained using a supervised learning approach with popular deep learning ...
Echrigui Rania, Hamiche Mhamed
doaj +1 more source
The proximal map of the weighted mean absolute error
PAMM, 2023 AbstractWe investigate the proximal map for the weighted mean absolute error function. An algorithm for its efficient and vectorized evaluation is presented. As a demonstration, this algorithm is applied to a nonsmooth energy minimization problem.
Lukas Baumgärtner +3 more
openaire +3 more sources
Analysis of time series for Malaysian currency exchange rate to the United States currency [PDF]
, 2021 Currency exchange rate is one of the external factors that will affect the financial status of Malaysia. Therefore, forecasting the foreign currency exchange rate is important for the financial decision makers, bankers, academic researchers and business ...
Che Him, Norziha +4 more
core +1 more source
Indian natural rubber price forecast–An Autoregressive Integrated Moving Average (ARIMA) approach
The Indian Journal of Agricultural Sciences, 2022 The objective of this study was to forecast the price of natural rubber in India during April 2019 to March 2020 by employing autoregressive integrated moving average (ARIMA).
SHYJU MATHEW, RAMASAMY MURUGESAN
doaj +1 more source
Quantitative Kinetic Energy Estimated from Disdrometer Signal [PDF]
, 2020 The kinetic energy of the rain drops was predicted in a relation between the rain rate and rain quantity, derived directly from the rain drop size distribution (DSD), which had been measured by a disdrometer located in the eastern state of Alagoas ...
Kwon, Byung-Hyuk +4 more
core +1 more source
A time series analysis for sales of chicken based food product [PDF]
, 2021 This study provides a time series analysis and interpretation of the output for forecast sales of chicken based food product of weekly sales data. These data were collected directly from the outlet shop of one factory in Malacca started from January 2015
Alma, Ozlem Gurunlu +5 more
core +1 more source
Mid-Term Residential Load Forecasting Based on Neighborhood Component Analysis Feature Selection [PDF]
هوش محاسباتی در مهندسی برق, 2022 Residential load forecasting plays an important role in management and planning in modern smart grids. In planning to keep demand and supply balanced, accurate residential load forecasting is needed.
Iman Bahadornejad +4 more
doaj +1 more source
Mean Absolute Percentage Error untuk Evaluasi Hasil Prediksi Komoditas Laut
JOINS (Journal of Information System), 2020 Volume ekspor komoditas gurita mengalami kenaikan dan stok di suatu daerah akan tidak merata dan berlebih, serta bahwa permintaan gurita di beberapa negara tujuan di Asia, Eropa dan Amerika telah meningkat secara signifikan.
Ida Nabillah, Indra Ranggadara
doaj +1 more source
The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation [PDF]
PeerJ Computer Science, 2021 Regression analysis makes up a large part of supervised machine learning, and consists of the prediction of a continuous independent target from a set of other predictor variables.
Davide Chicco +2 more
doaj +2 more sources