Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5102373 | Physica A: Statistical Mechanics and its Applications | 2018 | 18 Pages |
Abstract
This paper proposed a novel optimization method based on opinion formation in complex network systems. The proposed optimization technique mimics human-human interaction mechanism based on a mathematical model derived from social sciences. Our method encodes a subset of selected features to the opinion of an artificial agent and simulates the opinion formation process among a population of agents to solve the feature selection problem. The agents interact using an underlying interaction network structure and get into consensus in their opinions, while finding better solutions to the problem. A number of mechanisms are employed to avoid getting trapped in local minima. We compare the performance of the proposed method with a number of classical population-based optimization methods and a state-of-the-art opinion formation based method. Our experiments on a number of high dimensional datasets reveal outperformance of the proposed algorithm over others.
Related Topics
Physical Sciences and Engineering
Mathematics
Mathematical Physics
Authors
Homayoun Hamedmoghadam, Mahdi Jalili, Xinghuo Yu,