Review of metaheuristics inspired from the animal kingdom
EN Dragoi, V Dafinescu - Mathematics, 2021 - mdpi.com
The search for powerful optimizers has led to the development of a multitude of
metaheuristic algorithms inspired from all areas. This work focuses on the animal kingdom …
metaheuristic algorithms inspired from all areas. This work focuses on the animal kingdom …
[HTML][HTML] A comprehensive comparison among metaheuristics (MHs) for geohazard modeling using machine learning: Insights from a case study of landslide …
Abstract Machine learning (ML) has been extensively applied to model geohazards, yielding
tremendous success. However, researchers and practitioners still face challenges in …
tremendous success. However, researchers and practitioners still face challenges in …
A novel enhanced whale optimization algorithm for global optimization
One of the main issues with heuristics and meta-heuristics is the local optima stagnation
phenomena. It is often called premature convergence, which refers to the assumption of a …
phenomena. It is often called premature convergence, which refers to the assumption of a …
Parameters identification of photovoltaic models by using an enhanced adaptive butterfly optimization algorithm
W Long, T Wu, M Xu, M Tang, S Cai - Energy, 2021 - Elsevier
Establishing accurate and reliable models based on the measured data for photo-voltaic
(PV) modules are significant to design, control and evaluate the PV systems. Although many …
(PV) modules are significant to design, control and evaluate the PV systems. Although many …
mLBOA: A modified butterfly optimization algorithm with lagrange interpolation for global optimization
Abstract Though the Butterfly Bptimization Algorithm (BOA) has already proved its
effectiveness as a robust optimization algorithm, it has certain disadvantages. So, a new …
effectiveness as a robust optimization algorithm, it has certain disadvantages. So, a new …
Hybrid leader based optimization: a new stochastic optimization algorithm for solving optimization applications
M Dehghani, P Trojovský - Scientific Reports, 2022 - nature.com
In this paper, a new optimization algorithm called hybrid leader-based optimization (HLBO)
is introduced that is applicable in optimization challenges. The main idea of HLBO is to …
is introduced that is applicable in optimization challenges. The main idea of HLBO is to …
Dynamic butterfly optimization algorithm for feature selection
Feature selection represents an essential pre-processing step for a wide range of Machine
Learning approaches. Datasets typically contain irrelevant features that may negatively …
Learning approaches. Datasets typically contain irrelevant features that may negatively …
Swarm intelligence-based MPPT design for PV systems under diverse partial shading conditions
The photovoltaic (PV) system has attracted attention in recent years for generating more
power and freer from pollution and being eco-friendly to the environment. Nonetheless, the …
power and freer from pollution and being eco-friendly to the environment. Nonetheless, 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 …
Fitness–Distance Balance based adaptive guided differential evolution algorithm for security-constrained optimal power flow problem incorporating renewable energy …
One of the most difficult types of problems computationally is the security-constrained
optimal power flow (SCOPF), a non-convex, nonlinear, large-scale, nondeterministic …
optimal power flow (SCOPF), a non-convex, nonlinear, large-scale, nondeterministic …