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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 …
Review on parameter estimation techniques of solar photovoltaic systems
Beyond meeting power demand, switching to solar energy especially solar photovoltaic (PV)
offers many advantages like modularity, minimal maintenance, pollution free, and zero …
offers many advantages like modularity, minimal maintenance, pollution free, and zero …
A survey on new generation metaheuristic algorithms
Metaheuristics are an impressive area of research with extremely important improvements in
the solution of intractable optimization problems. Major advances have been made since the …
the solution of intractable optimization problems. Major advances have been made since the …
An improved moth flame optimization algorithm based on modified dynamic opposite learning strategy
Moth flame optimization (MFO) algorithm is a relatively new nature-inspired optimization
algorithm based on the moth's movement towards the moon. Premature convergence and …
algorithm based on the moth's movement towards the moon. Premature convergence and …
Greedy opposition-based learning for chimp optimization algorithm
The chimp optimization algorithm (ChOA) is a hunting-based model and can be utilized as a
set of optimization rules to tackle optimization problems. Although ChOA has shown …
set of optimization rules to tackle optimization problems. Although ChOA has shown …
Lens imaging opposition-based learning for differential evolution with cauchy perturbation
Opposition-based learning (OBL) is an effective optimization strategy that enhances the
performance of various global optimization algorithms. Among these algorithms, differential …
performance of various global optimization algorithms. Among these algorithms, differential …
Evolving chimp optimization algorithm by weighted opposition-based technique and greedy search for multimodal engineering problems
This paper presents an evolved chimp optimization algorithm (ChOA) that uses greedy
search (GS) and opposition-based learning (OBL) to respectively increase the ChOA's …
search (GS) and opposition-based learning (OBL) to respectively increase the ChOA's …
A multi-strategy enhanced sine cosine algorithm for global optimization and constrained practical engineering problems
Abstract The Sine Cosine Algorithm (SCA) has received much attention from engineering
and scientific fields since it was proposed. Nevertheless, when solving multimodal or …
and scientific fields since it was proposed. Nevertheless, when solving multimodal or …
Adaptive chaotic dynamic learning-based gazelle optimization algorithm for feature selection problems
Feature Selection (FS) is considered a crucial procedure for eliminating unnecessary
features from datasets. FS is considered a challenging problem that is difficult to solve …
features from datasets. FS is considered a challenging problem that is difficult to solve …
Biogeography-based optimization
D Simon - IEEE transactions on evolutionary computation, 2008 - ieeexplore.ieee.org
Biogeography is the study of the geographical distribution of biological organisms.
Mathematical equations that govern the distribution of organisms were first discovered and …
Mathematical equations that govern the distribution of organisms were first discovered and …