Chaotic-based Particle Swarm Optimization with Inertia Weight for Optimization Tasks

N. Mobaraki; R. Boostani; M. Sabeti

Volume 8, Issue 3 , July 2020, , Pages 303-312

https://doi.org/10.22044/jadm.2020.8594.1993

Abstract
  Among variety of meta-heuristic population-based search algorithms, particle swarm optimization (PSO) with adaptive inertia weight (AIW) has been considered as a versatile optimization tool, which incorporates the experience of the whole swarm into the movement of particles. Although the exploitation ...  Read More

H.3. Artificial Intelligence
Extracting Prior Knowledge from Data Distribution to Migrate from Blind to Semi-Supervised Clustering

Z. Sedighi; R. Boostani

Volume 6, Issue 2 , July 2018, , Pages 287-295

https://doi.org/10.22044/jadm.2017.5064.1611

Abstract
  Although many studies have been conducted to improve the clustering efficiency, most of the state-of-art schemes suffer from the lack of robustness and stability. This paper is aimed at proposing an efficient approach to elicit prior knowledge in terms of must-link and cannot-link from the estimated ...  Read More