This work focuses on the development of a parallel framework method to improve the effectiveness and the efficiency of the obtained solutions by Multi-objective Evolutionary Algori...
Dipankar Dasgupta, David Camilo Becerra Romero, Al...
The article describes a method combining two widely-used empirical approaches to learning from examples: rule induction and instance-based learning. In our algorithm (RIONA) decisi...
In the design of highly complex, heterogeneous, and concurrent systems, deadlock detection and resolution remains an important issue. In this paper, we systematically analyze the ...
Xi Chen, Abhijit Davare, Harry Hsieh, Alberto L. S...
Abstract. The performance of financial forecasting with neural networks dependents on the particular training set. We design mean-change-point test to divide the original dataset i...
To reduce the manual effort of assessing potential affected program parts during software evolution, we develop a tool, called Celadon, which automates the change impact analysis ...