Critical power prediction using SVM algorithms

Bankruptcy Prediction using SVM and Hybrid SVM Survey

Bankruptcy prediction has been a topic of active research for business and corporate organizations since past decades. It is an effective tool to help financial institutions and relevant people to make the right decision in investments, especially in the current competitive environment. The tool provides auditors and managers a chance to identify the problems early.

Prediction of cystine connectivity using SVM

One of the major contributors to protein structures is the formation of disulphide bonds between selected pairs of cysteines at oxidized state. Prediction of such disulphide bridges from sequence is challenging given that the possible combination of cysteine pairs as the number of cysteines increases in a protein. Here, we describe a SVM (support vector machine) model for the prediction of cyst...

Precise Wind Power Prediction with SVM Ensemble Regression

In this work, we propose the use of support vector regression ensembles for wind power prediction. Ensemble methods often yield better classification and regression accuracy than classical machine learning algorithms and reduce the computational cost. In the field of wind power generation, the integration into the smart grid is only possible with a precise forecast computed in a reasonable time...

Critical Analysis of Secondary Structure Prediction Algorithms

Improved Svm and Ann in Incipient Fault Diagnosis of Power Transformers Using Clonal Selection Algorithms

Based on statistical learning theory (SLT), the support vector machine (SVM) is well recognized as a powerful computational tool for problems with nonlinearity having high dimensionalities. Solving the problem of feature and kernel parameter selection is a difficult task in machine learning and of high practical relevance in blurred fault diagnosis. We explored the feasibility of applying an ar...