In this paper, we propose a whale optimization algorithm-based ensemble learning algorithm (WOA-ELA) for multi-output power consumption prediction using a weighted ensemble approach. Firstly, we optimize the hyper-parameters of the base estimators using the WOA. Each base estimator's performance is...
The intrusion detection model is based on a whale optimization algorithm (WOA)-trained artificial neural network (ANN). The WOA is applied to initialize and adjust the weight vector of the ANN to achieve the minimum mean square error. The proposed WOA-ANN model can address the challenges of ...
meta-heuristic algorithmswhale optimization algorithmclusteringk-meansClustering is a powerful technique in data-mining, which involves identifing homogeneous groups of objects based on the values of attributes. Meta-heuristic algorithms such as particle swarm optimization, artificial bee colony, genetic ...
The whale optimization algorithm has received much attention since its introduction due to its outstanding performance. However, like other algorithms, the whale optimization algorithm still suffers from some classical problems. To address the issues of slow convergence, low optimization precision, and sus...
Whale Optimization Algorithm and Adaptive Neuro-Fuzzy Inference System: a hybrid method for feature selection and land pattern classificationAdaptive Neuro-Fuzzy Inference System (ANFIS) is a robust method in solving non-linear classification by employing a human-readable interpretation manner. This paper...
Section 4 provides an introduction to the multi-strategy whale optimization algorithm for optimizing semi-supervised extreme learning machines. Section 5 presents and analyzes the experimental results of MSWOA. Section 6 provides a detailed description of the application of the CEC2017 benchmark suite....
The whale optimization algorithm (WOA) is a nature-inspired metaheuristic optimization algorithm, which was proposed by Mirjalili and Lewis in 2016. This algorithm has shown its ability to solve many...
% The Whale Optimization Algorithm function [Leader_score,Leader_pos,Convergence_curve]=WOA(SearchAgents_no,Max_iter,lb,ub,dim,fobj) % initialize position vector and score for the leader Leader_pos=zeros(1,dim); Leader_score=inf; %change this to -inf for maximization problems ...
International Journal of Computational Intelligence Systems https://doi.org/10.1007/s44196-023-00295-6 RESEARCH ARTICLE (2023) 16:115 WPO: A Whale Particle Optimization Algorithm Ko‑Wei Huang1 · Ze‑Xue Wu1 · Chang‑Long Jiang1 · Zih‑Hao Huang1 · Shih‑...
The Beluga Whale Optimization (BWO) is a meta-heuristic algorithm that simulates the life behavior of beluga whales. Aiming at the shortcomings of the BWO, such as poor solution accuracy, insufficient robust performance, and weak ability to jump out of local trap, this paper proposes an improve...