The combinations of inductively coupled plasma-optical emission spectrometry (ICP-OES) and three classification algorithms, i.e., partial least squares discriminant analysis (PLS-DA), least squares support vector machine (LS-SVM) and soft independent modeling of class analogies (SIMCA), for discriminating different brands of Iranian bottled mineral waters, were explored. ICP-OES was used for th...

Extreme Support Vector Machine (ESVM) is a nonlinear robust SVM algorithm based on regularized least squares optimization for binary-class classification. In this paper, a novel algorithm for regression tasks, Extreme Support Vector Regression (ESVR), is proposed based on ESVM. Moreover, kernel ESVR is suggested as well. Experiments show that, ESVR has a better generalization than some other tr...

forecasting of municipal waste generation is a critical challenge for decision making and planning,because proper planning and operation of a solid waste management system is intensively affected by municipal solid waste (msw) streams analysis and accurate predictions of solid waste quantities generated. due to dynamic and complexity of solid waste management system, models by artificial intell...

objective: international diabetes organization estimates that there are 285 million people worldwide who suffer from diabetes, and this figure is expected to increase to 450 million in next 20 years. according to statistics issued by the world health organization, diabetes is considered among ten leading causes of death in world and its prevalence in the population is growing.this paper deals w...

microarray data have an important role in identification and classification of the cancer tissues. having a few samples of microarrays in cancer researches is always one of the most concerns which lead to some problems in designing the classifiers. for this matter, preprocessing gene selection techniques should be utilized before classification to remove the noninformative genes from the microa...

background: numerous studies used microarray gene expression data to extract metastasis-driving gene signatures for the prediction of breast cancer relapse. however, the accuracy and generality of the previously introduced biomarkers are not acceptable for reliable usage in independent datasets. this inadequacy is attributed to ignoring gene interactions by simple feature selection methods, due...

monitoring and controlling air quality parameters form an important subject of atmospheric and environmental research today due to the health impacts caused by the different pollutants present in the urban areas. the support vector machine (svm), as a supervised learning analysis method, is considered an effective statistical tool for the prediction and analysis of air quality. the work present...

classical lbp such as complexity and high dimensions of feature vectors that make it necessary to apply dimension reduction processes. in this paper, we introduce an improved lbp algorithm to solve these problems that utilizes fast pca algorithm for reduction of vector dimensions of extracted features. in other words, proffer method (fast pca+lbp) is an improved lbp algorithm that is extracted ...