Classification in imbalanced domains is a recent challenge in machine learning. We refer to imbalanced classification when data presents many examples from one class and few from ...
In this paper, we present an algorithm based on the GRASP metaheuristic for solving a dynamic assignment problem in a P2P network designed for sending real-time video over the Int...
Machine scheduling is a critical problem in industries where products are custom-designed. The wide range of products, the lack of previous experiences in manufacturing, and the s...
Juan Carlos Vidal, Manuel Mucientes, Alberto Bugar...
This paper addresses the application of a PCA analysis on categorical data prior to diagnose a patients data set using a Case-Based Reasoning (CBR) system. The particularity is th...
The Railway Traveling Salesman Problem (RTSP) is a practical extension of the classical traveling salesman problem considering a railway network and train schedules. We are given ...
In order to produce robots which can interact more effectively with humans we propose that it is necessary for their cognitive processes to be grounded in the same perceptual elem...
Artificial Immune Systems (AIS) constitute an emerging and promising field, and have been applied to pattern recognition and classification tasks to a limited extent so far. This ...
Aris Lanaridis, Vasileios Karakasis, Andreas Stafy...
Artificial Neural Networks for online learning problems are often implemented with synaptic plasticity to achieve adaptive behaviour. A common problem is that the overall learning...