Results 21 to 30 of about 1,934,800 (291)
Analysis Of Solar Power Generation Forecasting Using Machine Learning Techniques [PDF]
E3S Web of Conferences, 2021 Solar power is generated using photovoltaic (PV) systems all over the world. Because the output power of PV systems is alternating and highly dependent on environmental circumstances, solar power sources are unpredictable in nature. Irradiance, humidity,
Anuradha K. +4 more
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Non-Zero Crossing Point Detection in a Distorted Sinusoidal Signal Using Logistic Regression Model
Computers, 2022 Non-Zero crossing point detection in a sinusoidal signal is essential in case of various power system and power electronics applications like power system protection and power converters controller design.
Venkataramana Veeramsetty +2 more
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Selecting local models in multiple regression by maximizing power [PDF]
Metrika, 2008 This paper considers multiple regression procedures for analyzing the relationship between a response variable and a vector of covariates in a nonparametric setting where both tuning parameters and the number of covariates need to be selected. We introduce an approach which handles the dilemma that with high dimensional data the sparsity of data in ...
Schafer, Chad M., Doksum, Kjell A.
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Sparse Heteroscedastic Multiple Spline Regression Models for Wind Turbine Power Curve Modeling [PDF]
IEEE Transactions on Sustainable Energy, 2021 An accurate wind turbine power curve (WTPC) plays a vital role in wind power forecasting and wind turbine condition monitoring. There are two major shortcomings of current WTPC models that prevent more accurate WTPC estimation, limited nonlinear fitting ability and the lack of in-depth understanding of the complex characteristics of WTPC.
Yun Wang +7 more
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Power Analysis for Parameter Estimation in Structural Equation Modeling: A Discussion and Tutorial
Advances in Methods and Practices in Psychological Science, 2021 Despite the widespread and rising popularity of structural equation modeling (SEM) in psychology, there is still much confusion surrounding how to choose an appropriate sample size for SEM.
Y. Andre Wang, Mijke Rhemtulla
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A Mathematical Programming Approach for Integrated Multiple Linear Regression Subset Selection and Validation [PDF]
, 2020 Subset selection for multiple linear regression aims to construct a regression model that minimizes errors by selecting a small number of explanatory variables.
Cheong, Taesu +3 more
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Power prior distributions for regression models
Statistical Science, 2000 We propose a general class of prior distributions for arbitrary regression models. We discuss parametric and semiparametric models. The prior specification for the regression coefficients focuses on observ- able quantities in that the elicitation is based on the availability of his- torical data Do and a scalar quantity ao quantifying the uncertainty ...
Ibrahim, Joseph G., Chen, Ming-Hui
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Estimation of lacunarity using gamma regression model
Acta Scientiarum: Technology, 2019 In this study we evaluate estimated lacunarity in three different databases using the power (standard) and gamma model. Results showed that estimates of lacunarity using gamma regression model was superior to those with the power regression model.
Leandro Ricardo Rodrigues de Lucena +1 more
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Revista Colombiana de Estadística, 2017 Regression analysis is a technique widely used in different areas of human knowledge, with distinct distributions for the error term. It is the case, however, that regression models with the error term following a bimodal distribution are not common in ...
GUILLERMO MARTÍNEZ-FLÓREZ +2 more
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Shortcut model for predicting refrigeration cycle performance [PDF]
, 2015 Compression refrigeration systems are very widely used to provide cooling to sub-ambient processes. The power demand of the cycle depends strongly on the temperature at which cooling is required, the temperature at which the refrigerant is condensed, as ...
Emtir, M., Etoumi, Asma, Jobson, Megan
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