Motivated Support Vector Regression with Structural Prior Knowledge

Motivated Support Vector Regression using Structural Prior Knowledge

It’s known that incorporating prior knowledge into support vector regression (SVR) can help to improve the approximation performance. Most of researches are concerned with the incorporation of knowledge in the form of numerical relationships. Little work, however, has been done to incorporate the prior knowledge on the structural relationships among the variables (referred as to Structural Prio...

Support vector regression with random output variable and probabilistic constraints

Support Vector Regression (SVR) solves regression problems based on the concept of Support Vector Machine (SVM). In this paper, a new model of SVR with probabilistic constraints is proposed that any of output data and bias are considered the random variables with uniform probability functions. Using the new proposed method, the optimal hyperplane regression can be obtained by solving a quadrati...

Knowledge-Based Green’s Kernel for Support Vector Regression

This paper presents a novel prior knowledge-based Green’s kernel for support vector regression SVR . After reviewing the correspondence between support vector kernels used in support vector machines SVMs and regularization operators used in regularization networks and the use of Green’s function of their corresponding regularization operators to construct support vector kernels, a mathematical ...

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

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...