biomedical datasets usually include a large number of features relative to the number of samples. however, some data dimensions may be less relevant or even irrelevant to the output class. selection of an optimal subset of features is critical, not only to reduce the processing cost but also to improve the classification results. to this end, this paper presents a hybrid method of filter and wr...

estimation of the metal value in the metallic deposits is one of the important factors to evaluate the deposits in exploration studies andmineral processing. therefore, one accurate estimator is essential to obtain a fine insight into the accumulation of the ore body. thereare geostatistical methods for the estimation of the concentration of iron which performance of these models is complexity ...

acute myelogenous leukemia (aml) is a subtype of acute leukemia, which is characterized by the accumulation of myeloid blastsin the bone marrow. careful microscopic examination of stained blood smear or bone marrow aspirate is still the most significantdiagnostic methodology for initial aml screening and considered as the first step toward diagnosis. it is time-consuming and dueto the elusive n...

t his paper presents a new feature selection approach for automatically extracting   ms lesions in 3d mr images. presented method is applicable to different types of ms lesions. in this method, t1, t2 and flair images are firstly preprocessed. in the next phase, effective features to extract ms lesions are selected by using a genetic algorithm. the fitness function of the genetic algorithm is t...

random number generation is one of the human abilities. it is proven that the sequence of random numbers generated by people do not follow full randomness criteria. these numbers produced by brain activity seem to be completely non stationary. in this paper, we show that there is a distinction between the random numbers generated by different people who provides the discrimination capability, a...

Constitutive modeling of clay is an important research in geotechnical engineering. It is difficult to use precise mathematical expressions to approximate stress-strain relationship of clay. Artificial neural network (ANN) and support vector machine (SVM) have been successfully used in constitutive modeling of clay. However, generalization ability of ANN has some limitations, and application of...

Loan default evaluation and discrimination is a complicated issue because of its nonlinearity and uncertainty. Least square support vector machine (LS-SVM) has been successfully employed to solve regression and time series problem. This paper proposes a novel PSO-LS-SVM model based on the improved PSO algorithm to optimize parameters of LS-SVM, which is a new improved form by synthesizing the e...

We proposed the support vector machine (SVM)-based equalisation schemes for direct-sequence ultra wideband (UWB) systems. The severe intersymbol interference caused by the UWB channel was formulated as a pattern classification problem in the SVM-based equaliser, which operates in two main modes: training and detection. We also applied the least squares support vector classifiers (LS-SVCs) to re...

according to recent developments of predicting methodsin financial markets, and since the stock price is one of the mostimportant factors for investment decision-making, and its predictioncan play an important role in this field, the aim of this study is toprovide a model to predict the stock price movement with highaccuracy. accordingly, a hybrid model for predicting the stock pricemovement us...