Text clustering is one of the efficient unsupervised learning techniques used to partition a
huge number of text documents into a subset of clusters. In which, each cluster contains …

Water resource management is a complex engineering problem, due to the stochastic
nature of inflow, various demands and environmental flow downstream. With the increase in …

Searching for the (near) optimal subset of features is a challenging problem in the process of
feature selection (FS). In the literature, Swarm Intelligence (SI) algorithms show superior …

Since different features may require different costs, the cost-sensitive feature selection
problem become more and more important in real-world applications. Generally, it includes …

Selecting the most discriminative features is a challenging problem in many applications.
Bio-inspired optimization algorithms have been widely applied to solve many optimization …

Krill herd (KH) algorithm is a novel swarm-based optimization algorithm that imitates krill
herding behavior during the searching for foods. It has been successfully used in solving …

Bat algorithm is a population metaheuristic proposed in 2010 which is based on the
echolocation or bio-sonar characteristics of microbats. Since its first implementation, the bat …

Text document clustering is to divide textual contents into clusters or groups. It received wide
attention due to the vast amount of daily data from the Web. In the last decade, Meta …

Misclassification costs of minority class data in real-world applications can be very high. This
is a challenging problem especially when the data is also high in dimensionality because of …

In this work, a new metaheuristic, Yin-Yang-Pair Optimization (YYPO), is proposed which is
based on maintaining a balance between exploration and exploitation of the search space. It …