Sentence examples for multiple nonlinear regression from inspiring English sources

Two multiple nonlinear regression models were developed.

Also, derived forms of Page and Diffusion equations have been used to obtain an equation containing both drying time and temperature by multiple nonlinear regression analysis.

Test results of the ANN and ANFIS models were compared with multiple nonlinear regression, multiple linear regression and existing bond strength models.

The multiple nonlinear regression models following the parameters including curing time, fiber content, and cement content for predicting compressive strength as well as tensile strength were established.

In the present work, a multiple nonlinear regression model is developed for predicting the fly ash dosage necessary to mitigate ASR per CPT.

In order to optimize the lapping parameters with a success, firstly, multiple nonlinear regression analyzes of experimental data were performed in terms of process parameters.

The performance of the ANN model is compared with multiple nonlinear and linear regression models.

It is found that the ANFIS model with RMSE of 0.0699 in validation stage is superior in estimation of discharge coefficient than the multiple nonlinear and linear regression models with RMSE of 0.1019 and 0.1507, respectively.

It was found that the ANN model with RMSE of 0.0674 in validation stage is superior in estimation of discharge coefficient than the multiple nonlinear and linear regression models with RMSE of 0.1019 and 0.1507, respectively.

The performance of the ANFIS model is compared Multiple Linear Regression (MLR) and Nonlinear Regression (NLR) models based on performance evaluation parameters.

Such a relationship is commonly referred to as a profile and may be represented by a simple linear, a multiple linear, a polynomial, or a nonlinear regression model.