In most traditional machine learning algorithms, the training and testing datasets have
identical distributions and feature spaces. However, these assumptions have not held in …

This chapter reviews applications of Memetic Algorithms in the areas of business analytics
and data science. This approach originates from the need to address optimization problems …

Online social networks have provided an appropriate infrastructure for users to interact with
one another and share information. Since trust is one of the most important factors in forming …

This book is written for computer engineers, scientists, and students studying/working in
reinforcement learning and artificial intelligence domains. The book collects recent …

This paper presents a multi-population differential evolution algorithm to address dynamic
optimization problems. In the proposed approach, a cellular learning automaton adjusts the …

Community structure is an important feature in complex networks which has great significant
for organization of networks. The community detection is the process of partitioning the …

Since online social networks usually have quite huge size and limited access, smaller
subgraphs of them are often produced and analysed as the representative samples of …

One of the problems with traditional genetic algorithms (GAs) is premature convergence,
which makes them incapable of finding good solutions to the problem. The memetic …

Nowadays, many systems can be well represented by multiplex networks, in which entities
can communicate with each other on multiple layers. A multiplex network under each layer …

Unlike the computational mechanisms of the past many decades, that involved individual
(extremely powerful) computers or clusters of machines, cloud computing (CC) is becoming …