PREDICTING THE PRICE OF CRYPTOCURRENCY USING SUPPORT VECTOR REGRESSION METHODS

Tehran Stock Price Modeling and Forecasting Using Support Vector Regression (SVR) and Its Comparison with the Classic Model ARIMA

Application of Support Vector Machine Regression for Predicting Critical Responses of Flexible Pavements

This paper aims to assess the application of Support Vector Machine (SVM) regression in order to analysis flexible pavements. To this end, 10000 Four-layer flexible pavement sections consisted of asphalt concrete layer, granular base layer, granular subbase layer, and subgrade soil were analyzed under the effect of standard axle loading using multi-layered elastic theory and pavement critical r...

The Porosity Prediction of One of Iran South Oil Field Carbonate Reservoirs Using Support Vector Regression

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...

Predicting Price of Taiwan Real Estates By Neural Networks and Support Vector Regression

Abstrac The main purpose of this study is to predict the real estate price in Taiwan efficiently. Neural networks and Support Vector Regression are applied and compared. Variables are first selected from previous research and than chose by stepwise procedure and trial-and-error methods. It is found that SVR with trial-and-error method performed the best with MAPE=4.466% and R=0.8540. In additio...

Comparison of classic regression methods with neural network and support vector machine in classifying groundwater resources

In the present era, classification of data is one of the most important issues in various sciences in order to detect and predict events. In statistics, the traditional view of these classifications will be based on classic methods and statistical models such as logistic regression. In the present era, known as the era of explosion of information, in most cases, we are faced with data that c...