This article uses support vector machines, logistics regression, and other methods for the comprehensive evaluation of credit decision-making small, medium, microenterprises comprehensively software programming such as MATLAB SPSS Modeler to solve problem. The results, risk index system, classification model, are obtained. Finally, this starts from decision provides theoretical practical sugges...

Reservoir permeability is a critical parameter for characterization of the hydrocarbon reservoirs. In fact, determination of permeability is a crucial task in reserve estimation, production and development. Traditional methods for permeability prediction are well log and core data analysis which are very expensive and time-consuming. Well log data is an alternative approach for prediction of pe...

Run off resulted from rainfall is the main way of receiving water in most parts of the World. Therefore, prediction of runoff volume resulted from rainfall is getting more and more important in control, harvesting and management of surface water. In this research a number of machine learning and data mining methods including support vector machines, regression trees (CART algorithm), model tree...

In this paper, a new image denoising method based on wavelet analysis and support vector machine regression (SVR) is presented. The feasibility of image denoising via support vector regression is discussed and an illustrative example is given. The wavelet kernel is proposed to construct wavelet support vector machine (WSVM). The result of experiment shows that the denoising method based on WSVM...

Porosity is considered as an important petrophysical parameter in characterizing reservoirs, calculating in-situ oil reserves, and production evaluation. Nowadays, using intelligent techniques has become a popular method for porosity estimation. Support vector machine (SVM) a new intelligent method with a great generalization potential of modeling non-linear relationships has been introduced fo...