A multi-channel piezoelectric quartz crystal sensor with a homemade computer interface was prepared and employed in the present study to detect mixture of organic molecules. Back propagation neural network (BPN) was used to distinguish the species in the mixture organic molecules and multivariate linear regression analysis (MLR) was used to compute the concentration of the species. A six-channe...

One of the essential sectors of Myanmar economy is agriculture which is sensitive to climate variation. The most important climatic element which impacts on agriculture sector is rainfall. Thus rainfall prediction becomes an important issue in agriculture country. Multi variables polynomial regression (MPR) provides an effective way to describe complex nonlinear input output relationships so th...

The objective of this study is to develop a method based on multivariate relevance vector regression (MVRVR) as a kernel-based Bayesian model for the estimation of above-ground biomass (AGB) in the Hyrcanian forests of Iran. Field AGB data from the Hyrcanian forests and multi-temporal PALSAR backscatter values are used for training and testing the methods. The results of the MVRVR method are th...

This study revisits the face-to-tongue articulatory inversion problem in speech. We compare the Multi Linear Regression method (MLR) with two more sophisticated methods based on Hidden Markov Models (HMMs) and Gaussian Mixture Models (GMMs), using the same French corpus of articulatory data acquired by ElectroMagnetoGraphy. GMMs give overall results better than HMMs, but MLR does poorly. GMMs a...

A quantitative structure-property relationship (QSPR) study is suggested for the prediction of retention times of volatile organic compounds. Various kinds of molecular descriptors were calculated to represent the molecular structure of compounds. Modeling of retention times of these compounds as a function of the theoretically derived descriptors was established by multiple linear regression (...

This paper presents a classification-driven biomedical image retrieval approach by combining multiple visual and text features with a multi-response linear regression (MLR)-based meta-learner. Feature descriptors at different levels of image representation are often in diverse forms and complementary in nature. For modality detection of medical images, the MLR has been proposed as a trainable c...

In recent years using artificial neural networks has increased as powerful tool with capability to predict linear and nonlinear relationships in complex engineering problems. Using this toolbox has been significant in different civil engineering fields, especially hydrological problems for various important parameters with different variables and complex mathematical equation. Predict soil eros...

Quantitative structure-property relationship (QSPR) analysis has been directed to a series of pure nonionic surfactants containing linear alkyl, cyclic alkyl, and alkey phenyl ethoxylates. Modeling of cloud point of these compounds as a function of the theoretically derived descriptors was established by multiple linear regression (MLR) and partial least squares (PLS) regression. In this study,...