Results 21 to 30 of about 406,624 (295)
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
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Using intelligent optimization methods to improve the group method of data handling in time series prediction [PDF]
, 2008 In this paper we show how the performance of the basic algorithm of the Group Method of Data Handling (GMDH) can be improved using Genetic Algorithms (GA) and Particle Swarm Optimization (PSO).
A. Episcopos +7 more
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Moments and root-mean-square error of the Bayesian MMSE estimator of classification error in the Gaussian model [PDF]
Pattern Recognition, 2014 The most important aspect of any classifier is its error rate, because this quantifies its predictive capacity. Thus, the accuracy of error estimation is critical. Error estimation is problematic in small-sample classifier design because the error must be estimated using the same data from which the classifier has been designed. Use of prior knowledge,
Amin Zollanvari, Edward R. Dougherty
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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
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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
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Optimal interpolation of satellite and ground data for irradiance nowcasting at city scales [PDF]
, 2017 We use a Bayesian method, optimal interpolation, to improve satellite derived irradiance estimates at city-scales using ground sensor data. Optimal interpolation requires error covariances in the satellite estimates and ground data, which define how ...
Alexander D. Cronin +24 more
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Root mean square error (RMSE) or mean absolute error (MAE): when to use them or not
Geoscientific Model Development, 2022 Abstract. The mean absolute error (MAE) and root mean squared error (RMSE) are widely used metrics for evaluating models. Yet, there remains enduring confusion over their use, such that a standard practice is to present both, leaving it to the reader to decide.
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Oil price forecasting using gene expression programming and artificial neural networks [PDF]
, 2016 This study aims to forecast oil prices using evolutionary techniques such as gene expression programming (GEP) and artificial neural network (NN) models to predict oil prices over the period from January 2, 1986 to June 12, 2012.
El-Masry, AA, Mostafa, M
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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 ...
Ryutaro TATEISHI, Chengang WEN
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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
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