Results 11 to 20 of about 467,408 (158)
Mean Absolute Percentage Error for regression models [PDF]
Neurocomputing, 2016 We study in this paper the consequences of using the Mean Absolute Percentage Error (MAPE) as a measure of quality for regression models. We prove the existence of an optimal MAPE model and we show the universal consistency of Empirical Risk Minimization based on the MAPE.
de Myttenaere, Arnaud +3 more
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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.
Frías Paredes, Laura +3 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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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
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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
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Forecasting the Beef Meat Prices in Erbil Using Box-Jenkins Models
Eurasian Journal of Management & Social Sciences, 2020 Foodstuff has a crucial role for everybody life in the world. In Iraq, beef meat is one of the important parts of the food basket of every household in Erbil.
Feink Mohammed Omer, Wasfi Tahir Salih
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Forecasting with Competing Models of Daily Bitcoin Price in R [PDF]
Journal of Studies in Social Sciences and Humanities, 2022 Bitcoin price exhibits patterns predictable on its historical pasts. We adopt ARIMA(auto), ARIMA(fix)models and the Holt-Winters filter (HWF) with trend plus additive seasonal HWF (𝛾[0,1]), and no seasonality HWF (𝛾[False]) to forecast the price of ...
Oluwatobi A. Adekunle +2 more
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A Prediction Model of Power Consumption in Smart City Using Hybrid Deep Learning Algorithm
JOIV: International Journal on Informatics Visualization, 2023 A smart city utilizes vast data collected through electronic methods, such as sensors and cameras, to improve daily life by managing resources and providing services. Moving towards a smart grid is a step in realizing this concept.
Salam Abdulkhaleq Noaman +2 more
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Forecasting Error Calculation with Mean Absolute Deviation and Mean Absolute Percentage Error
Journal of Physics: Conference Series, 2017 Prediction using a forecasting method is one of the most important things for an organization, the selection of appropriate forecasting methods is also important but the percentage error of a method is more important in order for decision makers to adopt the right culture, the use of the Mean Absolute Deviation and Mean Absolute Percentage Error to ...
Ummul Khair +3 more
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