Predicting of Surface Ozone Using Artificial Neural Networks and Support Vector Machines

Application of Artificial Neural Networks and Support Vector Machines for carbonate pores size estimation from 3D seismic data

This paper proposes a method for the prediction of pore size values in hydrocarbon reservoirs using 3D seismic data. To this end, an actual carbonate oil field in the south-western part ofIranwas selected. Taking real geological conditions into account, different models of reservoir were constructed for a range of viable pore size values.  Seismic surveying was performed next on these models. F...

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...

Application of Artificial Neural Networks in a Two-step Classification for Acute Lymphocytic Leukemia Diagnosis by Blood Lamella Images

Introduction: This study aimed to present a system based on intelligent models that can enhance the accuracy of diagnostic systems for acute leukemia. The three parts including preprocessing, feature extraction, and classification network are considered as associated series of actions. Therefore, any dysfunction or poor accuracy in each part might lead in general dysfunction of...

Prediction of Missing Data for Ozone Concentrations using Support Vector Machines and Radial Basis Neural Networks

In this paper we present results from prediction of data for ozone (O3) concentrations in ambient air by using the modelling techniques of support vector machines (SVM) and radial basis neural networks (RBF NN). The predictions are performed for two short periods of time: for 24 hours and for one week in August and in December in 2005, in Skopje, Macedonia. The built SVM models use different ki...