نتایج جستجو برای: multiple linear regressions mlr
تعداد نتایج: 1203338 فیلتر نتایج به سال:
In this work the electrooxidation half-wave potentials of some Benzoxazines were predicted from their structural molecular descriptors by using quantitative structure-property relationship (QSAR) approaches. The dataset consist the half-wave potential of 40 benzoxazine derivatives which were obtained by DC-polarography. Descriptors which were selected by stepwise multiple selection procedure ar...
The solvatochromism of fluoresceine and its derivatives was studied in solvents of different Hydrogen Bond Donor (HBD), Hydrogen Bond Acceptor (HBA), Donor Number (DN) and Acceptor Number (AN) by their UV-Vis spectra. Results showed that position, intensity and shape of absorption bands change with type of solvent. These changes can be rationalized by solvatochromic parameters such as ...
physiographic characteristics and climatic conditions are factors which contributing to river flow regime and understanding of relations between these factors and river flow in a basin result in its application for the ungauged sub-basins river flow prediction. in this research the relation between physiographic and climatic parameters of golestan province and rivers flow were examined by appli...
Simple slopes, regions of significance, and confidence bands are commonly used to evaluate interactions in multiple linear regression (MLR) models, and the use of these techniques has recently been extended to multilevel or hierarchical linear modeling (HLM) and latent curve analysis (LCA). However, conducting these tests andplotting the conditional relations is often a tedious and error-prone ...
In this paper, we present a statistical method based on GMM modeling to map the acoustic speech spectral features to visual features of Cued Speech in the regression criterion of Minimum Mean-Square Error (MMSE) in a low signal level which is innovative and different with the classic text-to-visual approach. Two different training methods for GMM, namely Expecting-Maximization (EM) approach and...
Large-area assessment of aboveground tree biomass (AGB) to inform regional or national forest monitoring programs can be efficiently carried out by combining remotely sensed data and field sample measurements through a generic statistical model, in contrast to site-specific models. We integrated forest inventory plot data with spatial predictors from Landsat time-series imagery and LiDAR strip ...
Predicting the mass of solid waste generation plays an important role in integrated solid waste management plans. In this study, the performance of two predictive models, Artificial Neural Network (ANN) and Multiple Linear Regression (MLR) was verified to predict mean Seasonal Municipal Solid Waste Generation (SMSWG) rate. The accuracy of the proposed models is illustrated through a case study ...
A linear quantitative structure-activity relationship (QSAR) model is presented for modeling and predicting induction of apoptosis by 4-aryl-4H-chromenes. The model was produced by using the multiple linear regression (MLR) technique on a database that consists of 43 recently discovered 4-aryl-4H-chromenes. Among the 61 different physicochemical, topological, and structural descriptors that wer...
A study using 51 wheat, 56 barley and 34 oat grain samples was conducted to investigate the feasibility of predicting the apparent metabolizable energy (AME) value of these cereals for poultry. Stepwise regression analyses were performed to evaluate the relationship of AME with starch, ether extract (EE), crude fiber (CF), soluble sugar (SS), ash and crude protein (CP) (for wheat and barley gra...
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