Particle Swarm Optimization Algorithm with a Bio-Inspired Aging Model

A Particle Swarm Optimization with a Bio-inspired Aging Model (BAM-PSO) algorithm is proposed to alleviate the premature convergence problem of other PSO algorithms. Each particle within the swarm is subjected to aging based on the age-related changes observed in immune system cells. The proposed algorithm is tested with several popular and well-established benchmark functions and its performance is compared to other evolutionary algorithms in both low and high dimensional scenarios. Simulation results reveal that at the cost of computational time, the proposed algorithm has the potential to solve the premature convergence problem that affects PSO-based algorithms; showing good results for both low and high dimensional problems. This work suggests that aging mechanisms do have further implications in computational intelligence

Bio-inspired aging model-particle swarm optimization and geometric algebra for structure from motion

On computer vision field Structure from Motion (SfM) algorithms offer good advantages for numerous applications (augmented reality, autonomous navigation, motion capture, remote sensing, object recognition, image-base 3D modeling, among others), nevertheless, these algorithms show some weakness; in the present paper we propose the use of Bio-inspired Aging Model-PSO (BAM-PSO) to improve the accuracy of SfM algorithms. The BAM-PSO algorithm is used over a Geometric Algebra (GA) framework in order to compute the rigid movement on images and this allows us to obtain a numerically stable algorithm. © Springer International Publishing Switzerland 2014

Bio-inspired aging model-particle swarm optimization and geometric algebra for structure from motion

On computer vision field Structure from Motion (SfM) algorithms offer good advantages for numerous applications (augmented reality, autonomous navigation, motion capture, remote sensing, object recognition, image-base 3D modeling, among others), nevertheless, these algorithms show some weakness; in the present paper we propose the use of Bio-inspired Aging Model-PSO (BAM-PSO) to improve the accuracy of SfM algorithms. The BAM-PSO algorithm is used over a Geometric Algebra (GA) framework in order to compute the rigid movement on images and this allows us to obtain a numerically stable algorithm. Zapotitlán Springer International Publishing Switzerland 2014