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...

a method based on electrical capacitance tomography (ect) and an improved least squares support vector machine (ls-svm) is proposed for void fraction measurement of oil-gas two-phase flow. in the modeling stage, to solve the two problems in ls-svm, pruning skills are employed to make ls-svm sparse and robust; then the real-coded genetic algorithm is introduced to solve the difficult problem of ...

recently, hardware sensors are widely used in monitoring and measurement of water quality parameters. constraint of the instrument to measure some water quality parameters such as the 5-day biochemical oxygen demand (bod5), which are time consuming, causes efforts are diverted to the use of software sensors for online prediction of bod5. the main goal of this research is developing an appropria...

introduction: raman spectroscopy, that is a spectroscopic technique based on inelastic scattering of monochromatic light, can provide valuable information about molecular vibrations, so using this technique we can study molecular changes in a sample. material and methods: in this research, 153 raman spectra obtained from normal and dried skin samples. baseline and electrical noise were eliminat...

In this paper the accuracy of two machine learning algorithms including SVM and Bayesian Network are investigated as two important algorithms in diagnosis of Parkinson’s disease. We use Parkinson's disease data in the University of California, Irvine (UCI). In order to optimize the SVM algorithm, different kernel functions and C parameters have been used and our results show that SVM with C par...

a simple and rapid method for the determination of 137ba isotope abundances in water samples by inductively coupled plasma-optical emission spectrometry (icp-oes) coupled with least-squares support vector machine regression (ls-svm) is reported. by evaluation of emission lines of barium, it was found that the emission line at 493.408 nm provides the best results for the determination of 137ba a...

With the growth of different search engines, it becomes difficult for an user to search particular information effectively. If a search engine could provide domain specific information such as that confines only to a particular topicality, it is referred to as domain specific engine. Applying the ranking model trained for broad-based search to a domain specific search does not achieve good perf...

The optimal parameters of the support vector machine (SVM) are very important for accuracy modeling and generalization performance. The quantum particle swarm optimization (QPSO) algorithm takes on the characteristics of the rapid global optimization, scale chaos method provides the characteristics of the fast convergence and the SVM has the characteristics of the nonlinear fitting. These advan...