This chapter emphasizes on the role played by rough set theory (RST) within the broad field
of Machine Learning (ML). As a sound data analysis and knowledge discovery paradigm …

Feature extraction and feature selection are two important issues in sensor-based condition
monitoring of any engineering systems. In this study, acoustic emission signals were first …

In this paper we propose a new model of particle swarm optimization called two-step PSO.
The basic idea is to split the heuristic search performed by particles into two stages. We …

This paper presents new results of our continuous effort to develop a computer-aided
radiographic weld inspection system. The focus of this study is on improving accuracy by …

This paper presents an Ant Colony Optimization (ACO) approach for feature selection. The
challenge in the feature selection problem is the large search space that exists due to either …

In classification of a multispectral remote sensing image, it is usually difficult to obtain higher
classification accuracy if we only consider the image's spectral feature or texture feature …

Bees Algorithm (BA), a heuristic optimization procedure, represents one of the fundamental
search techniques is based on the food foraging activities of bees. This algorithm performs a …

This paper introduces the Dynamic Mesh Optimization meta-heuristic, which falls under the
evolutionary computation techniques. Moreover, we outline its application to the feature …

Statistical-based feature extraction has been typically used to purpose obtaining the
important features from the sky image for cloud classification. These features come up with …

The feature selection problem has been usually addressed through heuristic approaches
given its significant computational complexity. In this context, evolutionary techniques have …