The original whale optimization algorithm (WOA) has a low initial population quality and tends to converge to local optimal solutions. To address these challenges, this paper introduces an improved whale optimization algorithm called OLCHWOA, incorporating a chaos mechanism and an opposition-based ...
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 ...
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 ...
在多种群体智能算法中,鲸鱼优化算法(Whale Optimization Algorithm, WOA)因其原理简单、控制参数少、适应度高等优点,已被广泛应用到非线性优化[18]、自动控制[19]、电源规划[20]等不同领域,展示了该算法在解决复杂多参数优化问题中的有效性,在多维函数求解中具有良好的寻优反演特性。本文针对小角前向激光散射法中颗...
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...
A total of eight benchmark functions are used to test the performance of the algorithm and the results show that CWCWOA is indeed accurate and stable. Furthermore, the diverse chaotic maps are utilized to improve WOA to build a Chaotic Whale Optimization Algorithm (CWOA) [13] and [14]. ...
The Whale Optimization Algorithm (WOA) is recognized for its simplicity, few control parameters, and effective local optima avoidance. However, it struggles with global search efficiency and slow convergence. This paper introduces the Improved WOA (ImWOA) to overcome these challenges. Initially, ImWOA...
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...
Whale Optimization Algorithm (WOA), as a newly proposed swarm-based algorithm, has gradually become a popular approach for optimization problems in various engineering fields. However, WOA suffers from the poor balance of exploration and exploitation, and premature convergence. In this paper, a new ...