Results 231 to 240 of about 5,204,898 (289)

A novel nonlinear regression model of SVR as a substitute for ANN to predict conductivity of MWCNT-CuO/water hybrid nanofluid based on empirical data

Physica A: Statistical Mechanics and its Applications, 2019
An ideal regression method should have several characteristics including precision, accuracy and generalization. In many studies in the field of nanofluid, the precision of models is more highlighted.
A. Karimipour, Seyed Amin Bagherzadeh, A. Taghipour, A. Abdollahi, M. Safaei   +4 more
semanticscholar   +1 more source

Cooling load prediction and optimal operation of HVAC systems using a multiple nonlinear regression model

Energy and Buildings, 2019
Cooling load prediction is a critically important technology for ensuring energy conservation in cooling systems. Examples include advance air conditioning control, chiller startup, and controlling the number of chilled water pumps in operation.
Chengliang Fan, Yunfei Ding
semanticscholar   +1 more source

RETRACTED: A nonlinear regression analysis method based on Stakeholder Theory Model for performance evaluation of poverty reduction of agricultural operators

The International Journal of Electrical Engineering & Education, 2019
A nonlinear regression analysis method for performance evaluation of poverty reduction of agricultural operators based on Stakeholder Theory Model analysis was proposed to improve the effectiveness of performance evaluation of poverty reduction of a new ...
Zhenmin Wang
semanticscholar   +1 more source

Nonlinear regression: a hybrid model

Computers & Operations Research, 1999
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +1 more source

On Comparing Two Dependent Linear and Nonlinear Regression Models

Journal of Testing and Evaluation, 2018
Linear and nonlinear regression models are flexible methods of data analysis that may be appropriate whenever a quantitative response variable is to be examined in relationship to any other explanatory variables.
M. Mahmoudi
semanticscholar   +1 more source

Nonlinear regression applied to interval-valued data

Pattern Analysis and Applications, 2016
FRANCISCO De A T DE CARVALHO, De Carvalho Francisco De A T   +1 more
exaly   +2 more sources

Robust Nonlinear Regression

, 2018
Robust Nonlinear Regression: with Applications using R develops new methods in robust nonlinear regression and implements a set of objects and functions in S-language, under SPLUS and R software.
Hossein Riazoshams, H. Midi, G. Ghilagaber   +2 more
semanticscholar   +1 more source

Nonstationary nonlinear heteroskedasticity in regression [PDF]

Journal of Econometrics, 2007
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Joon Y. Park, Heetaik Chung
openaire   +1 more source

Nonlinear probabilistic latent variable regression models for soft sensor application: From shallow to deep structure

, 2020
Probabilistic latent variable regression models have recently caught much attention in the process industry, particularly for soft sensor applications.
Bingbing Shen, Le Yao, Zhiqiang Ge
semanticscholar   +1 more source

Nonlinear Regression Analysis of the Joint-Regression Model

Biometrics, 1997
Summary: The joint-regression model for two-way data assumes a linear relation between a continuous response and column effects. Standard methods for fitting the model condition on estimates of the column effects, but including column effects as covariates in the model results in a nonlinear estimation problem.
Ng, Meei Pyng, Grunwald, Gary K.
openaire   +2 more sources