Improving dendritic neuron model with dynamic scale-free network-based differential evolution
Some recent research reports that a dendritic neuron model (DNM) can achieve better
performance than traditional artificial neuron networks (ANNs) on classification, prediction …
performance than traditional artificial neuron networks (ANNs) on classification, prediction …
A reinforcement learning brain storm optimization algorithm (BSO) with learning mechanism
F Zhao, X Hu, L Wang, J Zhao, J Tang - Knowledge-Based Systems, 2022 - Elsevier
Brain storm optimization algorithm (BSO), which is inspired by brain storm process of
human, has been adopted as an efficient optimizer for various complex problems. A …
human, has been adopted as an efficient optimizer for various complex problems. A …
Optimizing the parameters of hybrid active power filters through a comprehensive and dynamic multi-swarm gravitational search algorithm
This paper introduces a dynamic comprehensive multi-swarm gravitational search algorithm
with non-uniform mutation (cdGSA-2m) for optimizing hybrid active power filter (HAPF) …
with non-uniform mutation (cdGSA-2m) for optimizing hybrid active power filter (HAPF) …
Comparative study on single and multiple chaotic maps incorporated grey wolf optimization algorithms
As a meta-heuristic algorithm that simulates the intelligence of gray wolves, grey wolf
optimizer (GWO) has a wide range of applications in practical problems. As a kind of local …
optimizer (GWO) has a wide range of applications in practical problems. As a kind of local …
Spherical search algorithm with adaptive population control for global continuous optimization problems
Spherical search algorithm (SSA) calculates the spherical boundary and generates new
solutions on it by two sub-populations jointly. Many researches have shown that SSA is a …
solutions on it by two sub-populations jointly. Many researches have shown that SSA is a …
Bio-inspired algorithms and its applications for optimization in fuzzy clustering
In recent years, new metaheuristic algorithms have been developed taking as reference the
inspiration on biological and natural phenomena. This nature-inspired approach for …
inspiration on biological and natural phenomena. This nature-inspired approach for …
Multi-operator opposition-based learning with the neighborhood structure for numerical optimization problems and its applications
Opposition-based learning (OBL) is an effective strategy that adjusts the population to
accelerate the convergence of the algorithm. However, OBL involves two phases …
accelerate the convergence of the algorithm. However, OBL involves two phases …
Swarm intelligence in data science: challenges, opportunities and applications
Abstract The Swarm Intelligence (SI) algorithms have been useful in solving multifaceted
optimization problems. SI Algorithms as the name suggests work on the simulation principle …
optimization problems. SI Algorithms as the name suggests work on the simulation principle …
Information entropy-based differential evolution with extremely randomized trees and LightGBM for protein structural class prediction
The discovery of protein tertiary structure is the basis of current genetic engineering,
medicinal design, and other biological applications. Protein structural class plays a …
medicinal design, and other biological applications. Protein structural class plays a …
Population interaction network in representative differential evolution algorithms: Power-law outperforms Poisson distribution
Differential evolution is a classical and effective evolutionary algorithm. In recent years,
many differential evolution variants have been proposed and achieved good results on …
many differential evolution variants have been proposed and achieved good results on …