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.
TERESA Leon +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
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
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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
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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
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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
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Developing Novel Robust Loss Functions-Based Classification Layers for DLLSTM Neural Networks
IEEE Access, 2023 In this paper, we suggest improving the performance of developed activation function-based Deep Learning Long Short-Term Memory (DLLSTM) structures by employing robust loss functions like Mean Absolute Error $(MAE)$ and Sum Squared Error $(SSE)$ to ...
Mohamad Abou Houran +5 more
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Indian Journal of Ophthalmology, 2022 This review article attempts to evaluate the accuracy of intraocular lens power calculation formulae in short eyes. A thorough literature search of PubMed, Embase, Cochrane Library, Science Direct, Scopus, and Web of Science databases was conducted for ...
Ankur K Shrivastava +4 more
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Automated and Optimized Regression Model for UWB Antenna Design
Journal of Sensor and Actuator Networks, 2023 Antenna design involves continuously optimizing antenna parameters to meet the desired requirements. Since the process is manual, laborious, and time-consuming, a surrogate model based on machine learning provides an effective solution.
Sameena Pathan +3 more
doaj +1 more source