Loading...
Search for:
two-approaches
0.005 seconds
Using a classifier pool in accuracy based tracking of recurring concepts in data stream classification
, Article Evolving Systems ; Volume 4, Issue 1 , 2013 , Pages 43-60 ; 18686478 (ISSN) ; Ahmadi, Z ; Beigy, H ; Sharif University of Technology
2013
Abstract
Data streams have some unique properties which make them applicable in precise modeling of many real data mining applications. The most challenging property of data streams is the occurrence of "concept drift". Recurring concepts is a type of concept drift which can be seen in most of real world problems. Detecting recurring concepts makes it possible to exploit previous knowledge obtained in the learning process. This leads to quick adaptation of the learner whenever a concept reappears. In this paper, we propose a learning algorithm called Pool and Accuracy based Stream Classification with some variations, which takes the advantage of maintaining a pool of classifiers to track recurring...
Genetic algorithm-based pore network extraction from micro-computed tomography images
, Article Chemical Engineering Science ; Volume 92 , 2013 , Pages 157-166 ; 00092509 (ISSN) ; Jamshidi, S ; Iglauer, S ; Boozarjomehry, R ; Sharif University of Technology
2013
Abstract
A genetic-based pore network extraction method from micro-computed tomography (micro-CT) images is proposed in this paper. Several variables such as the number, radius and location of pores, the coordination number, as well as the radius and length of the throats are used herein as the optimization parameters. Two approaches to generate the pore network structure are presented. Unlike previous algorithms, the presented approaches are directly based on minimizing the error between the extracted network and the real porous medium. This leads to the generation of more accurate results while reducing required computational memories. Two different objective functions are used in building the...