Results 241 to 250 of about 1,934,800 (291)

Comparative analysis of shallow and hybrid deep learning models for predicting the cooling efficiency of nanofluid-cooled photovoltaic panel across multiple materials. [PDF]

Sci Rep
Özdemir Y, Ziyadanoğulları NB, Bakış E, Acar E.   +3 more
europepmc   +1 more source

Early-stage environmental impact forecasting of chemicals and processes with machine learning and data analytics tools. [PDF]

Clean Technol Environ Policy
Appiah HD, Conway M, Patel J, McMahon M, Hesketh R, Yenkie KM.   +5 more
europepmc   +1 more source

Bridging the Scales via Personalized Cellular Modeling and Deep Phenotyping in Schizophrenia.

JAMA Psychiatry
Raabe FJ, Popovic D, Vetter C, Fischer LE, Hasanaj G, Karsli B, Schäfer TJ, Almeida V, Atella A, Gagliardi M, Boudriot E, Yakimov V, Trastulla L, Jiang T, Weyer C, Roell L, Moussiopoulou J, Krcmár L, Galinski S, Papazova I, Pogarell O, Hasan A, Schulte EC, Schmitt A, Koutsouleris N, Levina A, Wagner E, Rossner MJ, Papiol S, Falkai P, Keeser D, Ziller MJ, CDP Working Group.   +32 more
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Non-linear regression model for wind turbine power curve

Renewable Energy, 2017
Abstract In this article, a study of wind turbine power curve modelling is presented with application to a particular wind turbine of Seirijai wind farm in Lithuania. A non-linear regression model for wind turbine power curve approximation was proposed, which stands out with several advantages, such as fitting physical properties of wind turbine (i.e.
Mantas Marčiukaitis, Inga Žutautaitė, Linas Martišauskas, Benas Jokšas, Giedrius Gecevičius, Athanasios Sfetsos   +5 more
openaire   +3 more sources

Regression-based RTL power modeling

ACM Transactions on Design Automation of Electronic Systems, 2000
Register-transfer level (RTL) power estimation is a key feature for synthesis-based design flows. The main challenge in establishing a sound RTL power estimation methodology is the construction of accurate, yet efficient, models of the power dissipation of functional macros. Such models should be automatically built, and should produce reliable average
BOGLIOLO, ALESSANDRO, BENINI L., DE MICHELI G.   +2 more
openaire   +2 more sources

Regression Models for Behavioral Power Estimation

Integrated Computer-Aided Engineering, 1998
Behavioral power estimation is required to help the designer in making important architectural choices. In this work we propose an accurate and general behavioral power modeling approach especially suited for synthesis-based design ows making use of a library of hard macros implementing behavioral operators.
BENINI L, BOGLIOLO A, FAVALLI, Michele, DE MICHELI G.   +3 more
openaire   +4 more sources

The exponentiated power exponential semiparametric regression model

Communications in Statistics - Simulation and Computation, 2020
We propose a new semiparametric regression model with exponentiated power exponential errors using the B-spline basis for nonlinear effects.
Fábio Prataviera, Edwin M. M. Ortega, Gauss M. Cordeiro, Vicente G. Cancho   +3 more
openaire   +1 more source

Analysis of wind power curve modeling using multi-model regression

Wind Engineering, 2023
Wind power prediction is vital in renewable energy. Correct forecasts enable utility companies to optimize production and minimize costs. However, due to the intricate nature of wind patterns, making precise predictions is challenging. This article introduces a novel model combining Quantile Regression and Decision Tree Regression for forecasting wind
Vivek Kumar Patidar, Rajesh Wadhvani, Muktesh Gupta   +2 more
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Power analysis for multivariable Cox regression models

Statistics in Medicine, 2018
In power analysis for multivariable Cox regression models, variance of the estimated log‐hazard ratio for the treatment effect is usually approximated by inverting the expected null information matrix. Because, in many typical power analysis settings, assumed true values of the hazard ratios are not necessarily close to unity, the accuracy of this ...
Emil Scosyrev, Ekkehard Glimm
openaire   +3 more sources