Quantized Salp Swarm Algorithm (QSSA) for optimal feature selection
Metaheuristic algorithms are well-known and widely used strategies for tackling optimization
issues. Each has advantages and limitations and is frequently combined with other …
issues. Each has advantages and limitations and is frequently combined with other …
Hybrid PSO (SGPSO) with the Incorporation of discretization operator for training RBF neural network and optimal feature selection
Particle swarm optimization (PSO) is a computational method that emerged recently based
on swarm intelligence techniques for resolving optimization complications. The popularity …
on swarm intelligence techniques for resolving optimization complications. The popularity …
[HTML][HTML] An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction
Although the practicability of using wavelet neural networks (WNNs) in nonlinear function
approximation has been addressed extensively, selecting the optimal number of hidden …
approximation has been addressed extensively, selecting the optimal number of hidden …
An improved pathfinder algorithm (ASDR-PFA) based on adaptation of search dimensional ratio for solving global optimization problems and optimal feature selection
Pathfinder algorithm (PFA) is a recently introduced meta-heuristic technique that mimics the
cooperative behavior of animal groups in search of the best food area. PFA consists of two …
cooperative behavior of animal groups in search of the best food area. PFA consists of two …
A MapReduce hybridized spotted hyena optimizer algorithm for travelling salesman problem
Abstract The Traveling Salesman (TSP) problem is one of the most common basic problems
in the nondeterministic polynomial problems (NP-hard) category. TSP is a good …
in the nondeterministic polynomial problems (NP-hard) category. TSP is a good …
GMPP tracking of solar PV system using spotted hyena and quadratic approximation based hybrid algorithm under partially shaded conditions
The demand for clean and renewable energy is increasing due to environmental concerns.
Photovoltaic (PV) system is very popular from the renewable sources and its usage is …
Photovoltaic (PV) system is very popular from the renewable sources and its usage is …
An efficient arithmetic optimization algorithm for solving subset-sum problem
The Subset-Sum Problem (SSP) ensures a significant role in various practical applications,
which include cryptography and coding theory owing to the importance in the functionality of …
which include cryptography and coding theory owing to the importance in the functionality of …
Quantized Orthogonal Experimentation SSA (QOX-SSA): A Hybrid Technique for Feature Selection (FS) and Neural Network Training
The standard metaheuristics are commonly based on a single metaphorical model miming a
particular animal group's food-searching behaviour. As a result, the contributions of such …
particular animal group's food-searching behaviour. As a result, the contributions of such …
Design and applications of improved metaheuristic algorithms for neural network training
The success of nature-inspired evolving metaheuristic algorithms can be attributed to the
seemingly balanced arrangement of operators used aimed at seamless exploration and …
seemingly balanced arrangement of operators used aimed at seamless exploration and …
Improved chaotic grey wolf optimization for training neural networks
BV Ramana, N Panda, S Teja, H Mohapatra, AK Dalai… - 2023 - nopr.niscpr.res.in
This paper introduces one improved version of the Grey Wolf Optimization algorithm (GWO),
one of the newly established nature-inspired metaheuristic algorithms, and the suggested …
one of the newly established nature-inspired metaheuristic algorithms, and the suggested …