Results 51 to 60 of about 8,395,195 (223)
Modeling Properties with Artificial Neural Networks and Multilinear Least-Squares Regression: Advantages and Drawbacks of the Two Methods [PDF]
Applied Sciences, 2018 The mean molecular connectivity indices (MMCI) proposed in previous studies are used in conjunction with well-known molecular connectivity indices (MCI) to model eleven properties of organic solvents. The MMCI and MCI descriptors selected by the stepwise multilinear least-squares (MLS) procedure were used to perform artificial neural network (ANN ...
Jesus Vicente De Julián-Ortiz +2 more
openaire +4 more sources
Polymer International, EarlyView.Biosurfactant was produced by Pseudomonas aeruginosa using andiroba waste from Amazonia. A biosurfactant–alginate composite (Alg/BioS) was successfully synthesized via ionotropic gelation, and achieved up to 70% Cr6+ removal from water. Abstract Environmental contamination by heavy metals represents a significant challenge due to their persistence in ...
Paulo Diniz Austriaco +11 more
wiley +1 more source
Predicting Slope Stability Failure through Machine Learning Paradigms
ISPRS International Journal of Geo-Information, 2019 In this study, we employed various machine learning-based techniques in predicting factor of safety against slope failures. Different regression methods namely, multi-layer perceptron (MLP), Gaussian process regression (GPR), multiple linear regression ...
Dieu Tien Bui +4 more
doaj +1 more source
Environmental Monitoring and Assessment, 2022 A physiographic-based multilinear regression model supported by GIS was developed to estimate spatial rainfall variability in the Southwest Iberian Peninsula. The area study includes a wide diversity of landscape features and comprises four Portuguese regions and one Spanish province (totalizing 28,860 km2).
Verónica Ruiz-Ortiz +4 more
openaire +4 more sources
On Bayesian inference with conjugate priors for scale mixtures of normal distributions [PDF]
, 2010 Bayesian inference is considered for the multivariate regression model with distribution of the random responses belonging to the multivariate scale mixtures of normal distributions.
Ng, V.M.
core
Structural Concrete, EarlyView.Abstract The use of fiber reinforced concrete (FRC) in precast tunnel segments is among the most established and representative applications of this material. Over the past two decades, numerous tunnel linings were constructed with partial or total substitution of conventional steel reinforcement by fibers, this yielding to quantifiable benefits in ...
Vladimir Rusanov +4 more
wiley +1 more source
Calibration and Validation of a Measurements-Independent Model for Road Traffic Noise Assessment
Applied Sciences, 2023 The assessment of road traffic noise is very important for the health of people living in urban areas. Noise is usually assessed by field measurements, and predictive models play an important role when experimental data are not available.
Domenico Rossi +2 more
doaj +1 more source
Multivariate multilinear regression
, 2012 Conventional regression methods, such as multivariate linear regression (MLR) and its extension principal component regression (PCR), deal well with the situations that the data are of the form of low-dimensional vector.
Tao, D. +10 more
core +1 more source
Geoscience Data Journal, Volume 13, Issue 4, October 2026.This study demonstrates the application of machine learning models—Random Forest, XGBoost, and Multiple Linear Regression—to predict Total Organic Carbon (TOC) from well logs, significantly improving TOC prediction accuracy and reliability across diverse geological settings compared to traditional log‐based methods.
Haseeb Ahmad +6 more
wiley +1 more source
Data on some socio-economic parameters explaining the movement of extra-EU asylum seekers in Europe
Data in Brief, 2016 This article contains data concerning the movement of extra-EU asylum seekers in Europe. Data used in this paper were collected from the Eurostat database and the UNHCR database.
Silvia Angeloni
doaj +1 more source