Opposition-based Learning (OBL) is a new concept in machine learning, inspired from the
opposite relationship among entities. In 2005, for the first time the concept of opposition was …

Retinal diseases are a leading cause of blindness in developed countries, accounting for
the largest share of visually impaired children, working-age adults (inherited retinal …

Evolutionary algorithms (EAs) are well-known optimization approaches to deal with
nonlinear and complex problems. However, these population-based algorithms are …

With rapid advancements in machine learning, we consider the epistemological
opportunities presented by this novel tool for promoting organizational theory. Our paper …

This paper provides an alternative method for creating an optimal subset from features
which in turn represent the whole features through improving the moth-flame optimization …

In this paper, an enhanced version of the opposition-based differential evolution (ODE) is
proposed. ODE utilizes opposite numbers in the population initialization and generation …

Population initialization is a crucial task in evolutionary algorithms because it can affect the
convergence speed and also the quality of the final solution. If no information about the …

We propose a novel variation to biogeography-based optimization (BBO), which is an
evolutionary algorithm (EA) developed for global optimization. The new algorithm employs …

For many soft computing methods, we need to generate random numbers to use either as
initial estimates or during the learning and search process. Recently, results for evolutionary …

Gravitational search algorithm (GSA) is based on the law of gravity and interaction between
masses. In GSA, the searcher agents are a collection of masses, and their interactions are …