Owing to the development of DNA microarray technologies, it is possible to get thousands of expression levels of genes at once. If we make the effective classification system with such acquired data, we can predict the class of new sample, whether it is normal or patient. For the classification system, we can use many feature selection methods and classifiers, but a method cannot be superior to...

An ideal ensemble is composed of base classifiers that perform well and that have minimal overlap in their errors. Eliminating classifiers from an ensemble based on a criterion that reflects poor classification performance and error redundancy with peer classifiers can improve ensemble performance. The Diversity Networks method asymmetrically evaluates each pair of classifiers as a linear combi...

To perform any economic management of a petroleum reservoir in real time, a predictable and/or updateable model of reservoir along with uncertainty estimation ability is required. One relatively recent method is a sequential Monte Carlo implementation of the Kalman filter: the Ensemble Kalman Filter (EnKF). The EnKF not only estimate uncertain parameters but also provide a recursive estimat...