Opposition based learning: A literature review
Opposition-based Learning (OBL) is a new concept in machine learning, inspired from the
opposite relationship among entities. In 2005, for the first time the concept of opposition was …
opposite relationship among entities. In 2005, for the first time the concept of opposition was …
[HTML][HTML] Particle swarm optimisation: a historical review up to the current developments
The Particle Swarm Optimisation (PSO) algorithm was inspired by the social and biological
behaviour of bird flocks searching for food sources. In this nature-based algorithm …
behaviour of bird flocks searching for food sources. In this nature-based algorithm …
A review of opposition-based learning from 2005 to 2012
Q Xu, L Wang, N Wang, X Hei, L Zhao - Engineering Applications of …, 2014 - Elsevier
Diverse forms of opposition are already existent virtually everywhere around us, and utilizing
opposite numbers to accelerate an optimization method is a new idea. Since 2005 …
opposite numbers to accelerate an optimization method is a new idea. Since 2005 …
Development and application of quantum entanglement inspired particle swarm optimization
Abstract Particle Swarm Optimization has been extensively researched and applied to tackle
optimization problems due to the ease in implementation and less number of parameters to …
optimization problems due to the ease in implementation and less number of parameters to …
[HTML][HTML] Bio-inspired optimization: algorithm, analysis and scope of application
G Devika, AG Karegowda - Swarm Intelligence-Recent Advances …, 2023 - intechopen.com
In the last few years, bio-inspired optimization techniques have been widely adopted in
fields such as computer science, mathematics, and biology in order to optimize solutions …
fields such as computer science, mathematics, and biology in order to optimize solutions …
Quasi oppositional—Manta ray foraging optimization and its application to PID control of a pendulum system
AA Abdul Razak, ANK Nasir, NA Mhd Rizal… - Proceedings of the 12th …, 2022 - Springer
This paper presents an improved version of Manta Ray Foraging Optimization (MRFO).
MRFO is relatively a single objective optimization algorithm. It was inspired from the …
MRFO is relatively a single objective optimization algorithm. It was inspired from the …
Modified particle swarm optimization with student T mutation (STPSO)
Particle Swarm Optimization (PSO) is a recognized algorithm for optimization problems, but
suffers from premature convergence. To prevent PSO from stagnation in local minima we are …
suffers from premature convergence. To prevent PSO from stagnation in local minima we are …
Complex network analysis in PSO as an fitness landscape classifier
M Pluhacek, R Senkerik, AVJ Janostik… - 2016 IEEE Congress …, 2016 - ieeexplore.ieee.org
In this paper, an initial small-scale study is carried out. It is proposed that using the complex
network analysis it may be possible to make a classification of the fitness landscape type. A …
network analysis it may be possible to make a classification of the fitness landscape type. A …
Opposition based particle swarm optimization with student T mutation (OSTPSO)
Particle swarm optimization (PSO) is a stochastic algorithm, used for the optimization
problems, proposed by Kennedy [1] in 1995. PSO is a recognized algorithm for optimization …
problems, proposed by Kennedy [1] in 1995. PSO is a recognized algorithm for optimization …
A modified particle swarm optimization with dynamic mutation period
C Ratanavilisagul, B Kruatrachue - 2014 11th International …, 2014 - ieeexplore.ieee.org
The particle swarm optimization (PSO) is an algorithm that attempts to search for better
solution in the solution space by attracting particles to converge toward a particle with the …
solution in the solution space by attracting particles to converge toward a particle with the …