The whale optimization algorithm (WOA) is a new bio-inspired meta-heuristic algorithm which is presented based on the social hunting behavior of humpback whales. WOA suffers premature convergence that causes it to trap in local optima. In order to overcome this limitation of WOA, in this paper...
To avoid these possible adverse results, it is significant to take effective measures to improve the original algorithm. In this article, we propose an improved Whale Optimization Algorithm (IWOA) for optimizing parameters of the CNN model, which adopts a nonlinear convergence factor, adaptive ...
Notably, we propose an improved whale optimization algorithm (WOA-HA), which incorporates several improvement factors such as a chaotic Hénon map mechanism (HMM), adaptive coefficient vector (ACV), and a binary operator. To assess the effectiveness of our approach, we compare the performance of ...
The whale optimization algorithm (WOA) is a swarm-based metaheuristic technique that is often used in the field of dimensionality reduction. Among the various WOA-based feature selection techniques in the literature, not a single technology illuminates the stability issue of WOA. Stability is often ...
Similar to other swarm-based algorithms, the recently developed whale optimization algorithm (WOA) has the problems of low accuracy and slow convergence. It is also easy to fall into local optimum. Moreover, WOA and its variants cannot perform well enough in solving high-dimensional optimization ...
The whale optimization algorithm (WOA) has shown promise in addressing this challenge, but issues persist, including poor stability, low efficiency, and accuracy in COVID-19 threshold image segmentation. To tackle these issues, we introduce a Latin hypercube sampling initialization-based multi-strategy...
improved whale optimization algorithm and a multilayer perceptron. In the proposed model, weights and biases of the multilayer perceptron are updated using an improved whale optimization algorithm. The efficacy of the proposed optimized neural network has been tested on five benchmark stance detection ...
The white shark optimization algorithm (WSO) is a new meta-heuristic algorithm inspired by the hunting behavior of white sharks. The WSO is prone to enter a premature state when solving high-dimensional optimization problem, and the accuracy of the optimization results is low. Therefore, an impr...
To classify various sonar dataset, this paper proposes the use of the newly developed Whale Optimization Algorithm (WOA) algorithm for training Multi-Layer Perceptrons Neural Network (MLPs NN). Similar to other evolutionary classifiers, trapping in local minima, slow convergence rate, and non-real-...
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 improv...