Editorial Board
A Q-learning-based memetic algorithm for multi-objective dynamic software project scheduling
Software project scheduling is the problem of allocating employees to tasks in a software project. Due to the large scale of current software projects, many studies have investigated the use of optimization algorithms to find good software project ...
Independent Bayesian classifier combination based sign language recognition using facial expression
Automatic Sign Language Recognition (SLR) systems are usually designed by means of recognizing hand and finger gestures. However, facial expressions play an important role to represent the emotional states during sign language communication, has not yet ...
Softmax regression based deep sparse autoencoder network for facial emotion recognition in human-robot interaction
Deep neural network (DNN) has been used as a learning model for modeling the hierarchical architecture of human brain. However, DNN suffers from problems of learning efficiency and computational complexity. To address these problems, deep sparse ...
An eigenvector based center selection for fast training scheme of RBFNN
The Radial Basis Function Neural Network (RBFNN) model is one of the most popular Feedforward Neural Network architectures. Calculating the proper RBF centers efficiently is one of the key problems in the configuration of an RBFNN model. In previous ...
Canonical decomposition of belief functions based on Teugels representation of the multivariate Bernoulli distribution
A canonical decomposition of belief functions is a unique decomposition of belief functions into elementary pieces of evidence. Smets found an equivalent representation of belief functions, which he interpreted as a canonical decomposition. However, his ...
An extended intuitionistic fuzzy TOPSIS method based on a new distance measure with an application to credit risk evaluation
In the process of multi-criteria decision making (MCDM), decision makers or experts usually exploit quantitative or qualitative methods to evaluate the comprehensive performance of all alternatives on each criterion. How the decision-makers or the ...
Concept drift in e-mail datasets
Analysing concept drift for improving the accuracy of anti-spam filters.Spam defined as a set of messages whose topics are not interesting to a given user.Topic extraction, summarization and analysis of messages.Development of new evaluation strategies ...