Results 21 to 30 of about 932,989 (354)
Defense of the Least Squares Solution to Peelle’s Pertinent Puzzle
Algorithms, 2011 Generalized least squares (GLS) for model parameter estimation has a long and successful history dating to its development by Gauss in 1795. Alternatives can outperform GLS in some settings, and alternatives to GLS are sometimes sought when GLS exhibits ...
Nicolas Hengartner +4 more
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Load Forecasting Techniques for Power System: Research Challenges and Survey
IEEE Access, 2022 The main and pivot part of electric companies is the load forecasting. Decision-makers and think tank of power sectors should forecast the future need of electricity with large accuracy and small error to give uninterrupted and free of load shedding ...
Naqash Ahmad +3 more
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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.
D. Chicco, M. Warrens, Giuseppe Jurman
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Estimation of conditional mean squared error of prediction for claims reserving
Annals of Actuarial Science, 2018 This paper studies estimation of the conditional mean squared error of prediction, conditional on what is known at the time of prediction. The particular problem considered is the assessment of actuarial reserving methods given data in the form of run ...
M. Lindholm, F. Lindskog, Felix Wahl
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Evaluating Gaussian processes for matched-field processing localization using minimum mean squared error criterion [PDF]
JASA Express LettersGaussian processes (GPs) can densify and denoise sparsely sampled signals and have been applied in matched-field processing (MFP) localization to improve localization accuracy and robustness.
Shanru Lin +4 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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Data Science Journal, 2010 An alternative ratio-cum-product estimator of population mean using the coefficient of kurtosis for two auxiliary variates has been proposed. The proposed estimator has been compared with a simple mean estimator, the usual ratio estimator, a product ...
Rajesh Tailor +2 more
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Results in Control and OptimizationAn error-minimizing estimator is always preferred in model fittings. However, each error-minimizing estimator minimizes error differently. This paper combines four error-minimizing estimators, which are root mean-squared error, mean absolute error, root ...
Razik Ridzuan Mohd Tajuddin
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Estimating a Bounded Normal Mean Relative to Squared Error Loss Function [PDF]
Journal of Sciences, Islamic Republic of Iran, 2011 Let be a random sample from a normal distribution with unknown mean and known variance The usual estimator of the mean, i.e., sample mean is the maximum likelihood estimator which under squared error loss function is minimax and admissible ...
A. Karimnezhad
doaj
Comparative Analysis Using Multiple Regression Models for Forecasting Photovoltaic Power Generation
EnergiesEffective machine learning regression models are useful toolsets for managing and planning energy in PV grid-connected systems. Machine learning regression models, however, have been crucial in the analysis, forecasting, and prediction of numerous ...
Burhan U Din Abdullah +5 more
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