ArticleBiomimetics (Basel, Switzerland)2023
Towards an Optimal KELM Using the PSO-BOA Optimization Strategy with Applications in Data Classification.
Article in Biomimetics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
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- Secretary bird optimization algorithm based on quantum computing and multiple strategies improvement for KELM diabetes classification.Scientific reports · 2025Article
- Zebra optimization algorithm incorporating opposition-based learning and dynamic elite-pooling strategies and its applications.PloS one · 2025Article
- Heuristic Optimization Algorithm of Black-Winged Kite Fused with Osprey and Its Engineering Application.Biomimetics (Basel, Switzerland) · 2024Article
- Hybrid Multi-Objective Chameleon Optimization Algorithm Based on Multi-Strategy Fusion and Its Applications.Biomimetics (Basel, Switzerland) · 2024Article
- Two New Bio-Inspired Particle Swarm Optimisation Algorithms for Single-Objective Continuous Variable Problems Based on Eavesdropping and Altruistic Animal Behaviours.Biomimetics (Basel, Switzerland) · 2024Article
- FOX Optimization Algorithm Based on Adaptive Spiral Flight and Multi-Strategy Fusion.Biomimetics (Basel, Switzerland) · 2024Article
- A comprehensive survey of the application of swarm intelligent optimization algorithm in photovoltaic energy storage systems.Scientific reports · 2024Article
- Path Planning of Unmanned Aerial Vehicles Based on an Improved Bio-Inspired Tuna Swarm Optimization Algorithm.Biomimetics (Basel, Switzerland) · 2024Article
- A Multi-Objective Optimization Problem Solving Method Based on Improved Golden Jackal Optimization Algorithm and Its Application.Biomimetics (Basel, Switzerland) · 2024Article
- Gorilla optimization algorithm combining sine cosine and cauchy variations and its engineering applications.Scientific reports · 2024Article
- A Hierarchical Control Strategy for a Rigid-Flexible Coupled Hexapod Bio-Robot.Biomimetics (Basel, Switzerland) · 2023Article
- Multi-Parameter Auto-Tuning Algorithm for Mass Spectrometer Based on Improved Particle Swarm Optimization.Bioengineering (Basel, Switzerland) · 2023Article
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Authors and funding
5 authors.
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Abstract
The features of the kernel extreme learning machine-efficient processing, improved performance, and less human parameter setting-have allowed it to be effectively used to batch multi-label classification tasks. These classic classification algorithms must at present contend with accuracy and space-time issues as a result of the vast and quick, multi-label, and concept drift features of the developing data streams in the practical application sector. The KELM training procedure still has a difficulty in that it has to be repeated numerous times independently in order to maximize the model's generalization performance or the number of nodes in the hidden layer. In this paper, a kernel extreme learning machine multi-label data classification method based on the butterfly algorithm optimized by particle swarm optimization is proposed. The proposed algorithm, which fully accounts for the optimization of the model generalization ability and the number of hidden layer nodes, can train multiple KELM hidden layer networks at once while maintaining the algorithm's current time complexity and avoiding a significant number of repeated calculations. The simulation results demonstrate that, in comparison to the PSO-KELM, BBA-KELM, and BOA-KELM algorithms, the PSOBOA-KELM algorithm proposed in this paper can more effectively search the kernel extreme learning machine parameters and more effectively balance the global and local performance, resulting in a KELM prediction model with a higher prediction accuracy.
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