Results 11 to 20 of about 1,934,800 (291)
Power logit regression for modeling bounded data
Statistical Modelling, 2023 The main purpose of this article is to introduce a new class of regression models for bounded continuous data, commonly encountered in applied research. The models, named the power logit regression models, assume that the response variable follows a distribution in a wide, flexible class of distributions with three parameters, namely, the median, a ...
Queiroz, Francisco F. +1 more
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Applied Sciences, 2021 This study identified the meteorological variables that significantly impact the power generation of a solar power plant in Samcheonpo, Korea. To this end, multiple regression models were developed to estimate the power generation of the solar power ...
Young Seo Kim +4 more
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Experimental and analysis on household electronic power consumption
Energy Reports, 2022 Household power consumption helps the power supply department understand the power consumption of residents and whether there will be some abnormal power consumption phenomena.
Jing Qin
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IEEE Access, 2021 Photovoltaic (PV) power prediction has a constantly evolving solutions landscape with a myriad of data-driven techniques. Each technique leverages a self-adaptive algorithm that must retrain in intervals, be it each day, week, or season, to avoid the ...
Aditya Sundararajan, Ben Ollis
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Scientific African, 2023 In linear regression, a major problem arise when the response variable is bimodal. In this study, the non-linear effects of tourism development on the economic well-being of some selected emerging economies, which have bimodal features was modelled. In a
Olumide Metilelu +2 more
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Variations of power-expected-posterior priors in normal regression models [PDF]
Computational Statistics & Data Analysis, 2020 The power-expected-posterior (PEP) prior is an objective prior for Gaussian linear models, which leads to consistent model selection inference, under the M-closed scenario, and tends to favor parsimonious models. Recently, two new forms of the PEP prior were proposed which generalize its applicability to a wider range of models. The properties of these
Dimitris Fouskakis +2 more
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Multivariate Wind Turbine Power Curve Model Based on Data Clustering and Polynomial LASSO Regression
Applied Sciences, 2021 Wind turbine performance monitoring is a complex task because of the non-stationary operation conditions and because the power has a multivariate dependence on the ambient conditions and working parameters.
Davide Astolfi, Ravi Pandit
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Wind power curve modeling: A probabilistic Beta regression approach
Renewable Energy, 2023 Wind turbine power curves play a key role in various aspects during the life of a wind farm. Typical uses range from wind power forecasting to wind turbine condition monitoring. This paper addresses the identification of probabilistic models of wind power curves from observed data.
Marco Capelletti +2 more
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Austrian Journal of Statistics, 2023 In this article, we explore a new probability density function, called the power modified Lindley distribution. Its main feature is to operate a simple trade-off among the generalized exponential, Weibull and gamma distributions, offering an alternative
Omid Kharazmi, Devendra Kumar, Sanku Dey
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PLOS ONE, 2023 Wind turbine power curve (WTPC) serves as an important tool for wind turbine condition monitoring and wind power forecasting. Due to complex environmental factors and technical issues of the wind turbines, there are many outliers and inconsistencies present in the recorded data, which cannot be removed through any pre-processing technique. However, the
Khurram Mushtaq +6 more
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