Support Vector Neural Training

Support vector regression for prediction of gas reservoirs permeability

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...

Modeling and analysis of leishmaniasis distribution process using multilayer perceptron neural network and support vector regression (Case study: villages of Isfahan province)

Villages located in Isfahan province are one of the areas prone to the spread of cutaneous leishmaniasis, which is characterized by the occurrence of wounds on the skin. To predict the future prevalence of cutaneous leishmaniasis, Continuous monitoring of the spatial distribution of this disease is essential. Disease modeling was performed using two machine learning algorithms called support ve...

A Comparative Study of Extreme Learning Machines and Support Vector Machines in Prediction of Sediment Transport in Open Channels

The limiting velocity in open channels to prevent long-term sedimentation is predicted in this paper using a powerful soft computing technique known as Extreme Learning Machines (ELM). The ELM is a single Layer Feed-forward Neural Network (SLFNN) with a high level of training speed. The dimensionless parameter of limiting velocity which is known as the densimetric Froude number (Fr) is predicte...

A Comparative Approximate Economic Behavior Analysis Of Support Vector Machines And Neural Networks Models

Prediction of true critical temperature and pressure of binary hydrocarbon mixtures: A Comparison between the artificial neural networks and the support vector machine

Two main objectives have been considered in this paper: providing a good model to predict the critical temperature and pressure of binary hydrocarbon mixtures, and comparing the efficiency of the artificial neural network algorithms and the support vector regression as two commonly used soft computing methods. In order to have a fair comparison and to achieve the highest efficiency, a comprehen...

Bubble Pressure Prediction of Reservoir Fluids using Artificial Neural Network and Support Vector Machine

Bubble point pressure is an important parameter in equilibrium calculations of reservoir fluids and having other applications in reservoir engineering. In this work, an artificial neural network (ANN) and a least square support vector machine (LS-SVM) have been used to predict the bubble point pressure of reservoir fluids. Also, the accuracy of the models have been compared to two-equation stat...