Results 31 to 40 of about 5,661,692 (304)
Multi-region electricity demand prediction with ensemble deep neural networks.
PLoS ONE, 2023 Electricity consumption prediction plays a vital role in intelligent energy management systems, and it is essential for electricity power supply companies to have accurate short and long-term energy predictions.
Muhammad Irfan +9 more
doaj +1 more source
Journal of Marine Science and Engineering, 2023 The power load data of electric-powered ships vary with the ships’ operational status and external environmental factors such as sea conditions. Therefore, a model is required to accurately predict a ship’s power load, which depends on changes in the ...
Ji-Yoon Kim, Jin-Seok Oh
doaj +1 more source
Neutron optical test of completeness of quantum root-mean-square errors [PDF]
npj Quantum Information, 2021 AbstractWhile in classical mechanics the mean error of a measurement is solely caused by the measuring process (or device), in quantum mechanics the operator-based nature of quantum measurements has to be considered in the error measure as well. One of the major problems in quantum physics has been to generalize the classical root-mean-square error to ...
Stephan Sponar +3 more
openaire +4 more sources
Bootstrap for estimating the mean squared error of the spatial EBLUP [PDF]
, 2007 This work assumes that the small area quantities of interest follow a Fay-Herriot model with spatially correlated random area effects. Under this model, parametric and nonparametric bootstrap procedures are proposed for estimating the mean squared ...
Pratesi, Monica +2 more
core +1 more source
Decomposition of the mean absolute error (MAE) into systematic and unsystematic components.
PLoS ONE, 2023 When evaluating the performance of quantitative models, dimensioned errors often are characterized by sums-of-squares measures such as the mean squared error (MSE) or its square root, the root mean squared error (RMSE).
Scott M Robeson, Cort J Willmott
doaj +1 more source
Use of Machine Learning to Predict the Glycemic Status of Patients with Diabetes
Medical Sciences Forum, 2022 In this work, a machine learning methodology is used to predict the progress of the glycemic values of six patients with diabetes. Eight different algorithms are compared i.e., ANN, PNN, Polynomial Regression, Gradient Boosted Trees Regression, Random ...
Alessandro Massaro +4 more
doaj +1 more source
Root mean squared error of all six configurations of SCNN_12.
, 2022 Root mean squared error of all six configurations of SCNN_12.
Sidratul Montaha (13200394) +5 more
core +1 more source
Journal of Electrical Engineering and Computer, 2023 Penyakit hipertensi atau tekanan darah tinggi merupakan masalah kesehatan yang signifikan secara global. Prediksi yang akurat tentang risiko hipertensi dapat membantu dalam pencegahan, diagnosa, dan pengobatan dini. Dalam penelitian ini, kami mengusulkan
Sudriyanto Sudriyanto
doaj +1 more source
New Entropy Estimators with Smaller Root Mean Squared Error [PDF]
Journal of Modern Applied Statistical Methods, 2015 New estimators of entropy of continuous random variable are suggested. The proposed estimators are investigated under simple random sampling (SRS), ranked set sampling (RSS), and double ranked set sampling (DRSS) methods. The estimators are compared with
Al-Omari, Amer Ibrahim +1 more
openaire +3 more sources
Relationshio between Root Mean Square Error and Probable Error.
Journal of the Japan society of photogrammetry and remote sensing, 1994 The relationship between Root Mean Square (RMS) error and probable error was investigated under the condition of normal distribution with independent x, y and z error components. In the ideal case of no bias and equal standard deviations (in the case of two or three dimensions), the ratios of 90% probable error to RMS error are 1.645 (one dimensional ...
TATEISHI, Ryutaro, WEN, Chengang
openaire +2 more sources