Results 31 to 40 of about 1,079,927 (298)
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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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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Optimum design of chamfer masks using symmetric mean absolute percentage error
EURASIP Journal on Image and Video Processing, 2019 Distance transform, a central operation in image and video analysis, involves finding the shortest path between feature and non-feature entries of a binary image.
Baraka Jacob Maiseli
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Size Constrained Clustering With MILP Formulation
IEEE Access, 2020 Clustering is one of the essential tools for data mining since it reveals the natural structures of the unlabeled data. Many clustering algorithms have been proposed in the last decades.
Wei Tang +3 more
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Mean Squared Error (MSE) dan Penggunaannya
Jurnal Pengabdian MasyarakatMean Squared Error (MSE) adalah metrik evaluasi yang umum digunakan dalam statistik dan machine learning untuk mengukur seberapa akurat sebuah model regresi dalam memprediksi nilai numerik.
H. Nuha
semanticscholar +1 more source
Media StatistikaAnalysis of gene expression data, particularly in cancer data, often faces challenges due to the presence of missing values. One approach to overcome this is data imputation.
Mastika Mastika +2 more
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Higher Order Mean Squared Error of Generalized Method of Moments Estimators for Nonlinear Models
Discrete Dynamics in Nature and Society, 2014 Generalized method of moments (GMM) has been widely applied for estimation of nonlinear models in economics and finance. Although generalized method of moments has good asymptotic properties under fairly moderate regularity conditions, its finite sample ...
Yi Hu +3 more
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Mean squared error of empirical predictor
The Annals of Statistics, 2004 The term ``empirical predictor'' refers to a two-stage predictor of a linear combination of fixed and random effects. In the first stage, a predictor is obtained but it involves unknown parameters; thus, in the second stage, the unknown parameters are replaced by their estimators.
Das, Kalyan +2 more
openaire +3 more sources