A Hybrid Feature Selection Approach: β-Hill Climbing and Henry Gas Optimization

Abstract

Improved Henry gas solubility optimization algorithm is a better way to use an existing method (HGSO) inspired by gas dissolving in liquids, to find optimal solutions. It leverages the influence of pressure and temperature on gas solubility to guide their search for optimal solutions in optimization problems. It aims to overcome the limitations of the original Henry gas solubility optimization algorithm and enhance its performance in solving various optimization problems. It can be used in many applications, such as feature extraction, task scheduling, joint mining, and parameter optimization. This paper proposes a new approach called the β-Hill operator, which builds upon the traditional hill climbing method. to improve the balance between finding better solutions (exploitation) and exploring new possibilities (exploration).