Advances in spotted hyena optimizer: a comprehensive survey
S Ghafori, FS Gharehchopogh - Archives of computational methods in …, 2022 - Springer
Metaheuristic algorithms are widely used in various fields of optimization engineering.
These algorithms have become popular because of their ability to explore and exploit …
These algorithms have become popular because of their ability to explore and exploit …
Hybrid PSO (SGPSO) with the Incorporation of discretization operator for training RBF neural network and optimal feature selection
AK Mahapatra, N Panda, BK Pattanayak - Arabian Journal for Science and …, 2023 - Springer
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 …
A hybrid approach of spotted hyena optimization integrated with quadratic approximation for training wavelet neural network
Spotted hyena optimization (SHO) is one of the newly evolved swarm-based metaheuristic
optimization methods based on the social life cycle of hyenas. In recent times SHO is being …
optimization methods based on the social life cycle of hyenas. In recent times SHO is being …
Oppositional salp swarm algorithm with mutation operator for global optimization and application in training higher order neural networks
Effectiveness of any swarm based metaheuristic optimization algorithm focuses on perfect
mishmash of operator's castoff for exploration and exploitation. The absenteeism of balance …
mishmash of operator's castoff for exploration and exploitation. The absenteeism of balance …
Improved spotted hyena optimizer with space transformational search for training pi‐sigma higher order neural network
Spotted hyena optimizer (SHO) is a recently developed swarm‐based algorithm in the field
of metaheuristic research, for solving realistic engineering design constraint and …
of metaheuristic research, for solving realistic engineering design constraint and …
Oppositional spotted hyena optimizer with mutation operator for global optimization and application in training wavelet neural network
Success behind nature inspired evolutionary metaheuristic algorithms lies in its seemly
combination of operator's castoff for smooth balance between exploration and exploitation …
combination of operator's castoff for smooth balance between exploration and exploitation …
Effectiveness of swarm-based metaheuristic algorithm in data classification using pi-sigma higher order neural network
Abstract In this paper, Salp Swarm Algorithm (SSA) is employed in training the Higher Order
Neural Network (HONN) for data classification task. In machine learning approach, to train …
Neural Network (HONN) for data classification task. In machine learning approach, to train …
Data classification by ensemble methods in machine learning
G Jagadeeswara Rao, A Siva Prasad… - Advances in Intelligent …, 2022 - Springer
Diabetes is considered one critical disease, and majority of people are suffering from
diabetes. The cause of diabetes may be due to various factors like obesity, age, hereditary …
diabetes. The cause of diabetes may be due to various factors like obesity, age, hereditary …
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 …
Effectiveness of backpropagation algorithm in healthcare data classification
Nowadays, researchers are trying to reveal better consequences by acting on machine
learning (ML) algorithms. The notion behind this study is to represent the fundamental …
learning (ML) algorithms. The notion behind this study is to represent the fundamental …