Aleixandre-Tudó J.L., Alvarez I., García M.J., Lizama V., Aleixandre J.L. (2015): Application of multivariate regression methods to predict sensory quality of red wines. Czech J. Food Sci., 33: 217–227. Several multivariate methods including partial least squares (PLS) regression, principal component regression (PCR) or multiple linear regression (MLR) have been applied to predict wine quality,...

Effect coding is a coding scheme used when an analysis of variance (anova) is performed with multiple linear regression (mlr). With effect coding, the experimental effect is analyzed as a set of (nonorthogonal) contrasts which opposes all but one experimental conditions to one given experimental condition (usually the last one). With effect coding, the intercept is equal to the grand mean and t...

Urban agglomeration is the mainstream trend of urban development in world. It also main form new urbanization China and an important platform to participate international competition cooperation. The pattern industrial division labor has basically taken shape Chengdu Plain Economic Zone, cooperation system been gradually established. However, phenomenon isomorphism still prominent. In process p...

Wavelength selection is one of the key steps in quantitative spectral analysis, which reduces computation time while also improving prediction accuracy model. In this paper, we propose a wavelength algorithm based on ant colony optimization (ACO), absolute value regression coefficient multiple linear (MLR) model used as basis for evaluating importance wavelengths, and after full MLR modeling in...

We present a novel approach to improve the estimation of systolic (SBP) and diastolic blood pressure (DBP) from oscillometric waveform data using variable characteristic ratios between SBP and DBP with mean arterial pressure (MAP). This was verified in 25 healthy subjects, aged 28 ± 5 years. The multiple linear regression (MLR) and support vector regression (SVR) models were used to examine the...

The relationship between soil properties and environmental covariates is mostly nonlinear for human impacted areas. Herein, we proposed a model mapping organic carbon (SOC) total nitrogen (TN) in typical area (a small watershed of Poyang Lake, China), namely radial basis function neural network combined with agricultural land use (RBFNN_ALU). results showed that the RBFNN_ALU performs better th...

The present work describes a comparison of the ability of multiple linear regression (MLR) and artificial neural networks (ANN) to predict fish spatial occupancy and abundance in a mesotrophic reservoir. Models were run and tested with 306 observations obtained by the sampling point abundance method using electrofishing. For each of the 306 samples, the relationships between physical parameters...

Mediumand long-term runoff forecasting is essential for hydropower generation and water resources coordinated regulation in the Yellow River headwaters region. Climate change has a great impact on runoff within basins, and incorporating different climate information into runoff forecasting can assist in creating longer lead-times in planning periods. In this paper, a multimodel approach was dev...

We have improved the multiple linear regression (MLR) algorithm for protein secondary structure prediction by combining it with the evolutionary information provided by multiple sequence alignment of PSI-BLAST. On the CB513 dataset, the three states average overall per-residue accuracy, Q(3), reached 76.4%, while segment overlap accuracy, SOV99, reached 73.2%, using a rigorous jackknife procedu...