1、简介本文介绍一种新的全局优化算法——小龙虾优化算法Crayfish optimization algorithm(COA),模拟了小龙虾的避暑行为、竞争行为和觅食行为。该成果于2023年9月最新发表在Artifcial Intelligence Review。 CO…
Crayfish Optimization Algorithm (COA) is innovative and easy to implement, but the crayfish search efficiency decreases in the later stage of the algorithm, and the algorithm is easy to fall into local optimum. To solve these problems, this paper proposes an modified crayfish optimization algorithm...
Crayfish Optimization Algorithm (COA) is innovative and easy to implement, but the crayfish search efficiency decreases in the later stage of the algorithm, and the algorithm is easy to fall into local optimum. To solve these problems, this paper proposes an modified crayfish optimization algorithm...
To address this issue, this paper introduces a Hierarchical Learning-based Chaotic Crayfish Optimization Algorithm (HLCCOA) aimed at enhancing the generalization ability of ELMs. Initially, to resolve the problems of slow search speed and premature convergence typical of traditional crayfish optimization ...
engineering optimizationCrayfish optimization algorithm (COA) is a novel bionic metaheuristic algorithm with high convergence speed and solution accuracy. However, in some complex optimization problems and real application scenarios, the performance of COA is not satisfactory. In order to ...
This paper proposes a meta heuristic optimization algorithm, called Crayfish Optimization Algorithm (COA), which simulates crayfish's summer resort behavior, competition behavior and foraging behavior. The three behaviors are divided into three different stages to balance the exploration and exploitation ...
The crayfish optimization algorithm (COA), recently proposed as a meta-heuristic algorithm (MA), exhibits certain limitations such as imbalanced exploration and exploitation capacities, susceptibility to premature optimization, and a propensity for stagnation. To address these shortcomings, we incorporate ...
The Crayfish Optimization Algorithm (COA) is a new metaheuristic algorithm that has been proposed in recent years. While it has a strong local search ability, its global search ability is weak. this paper presents an improved version called ECOA. Firstly, a novel scaling factor is introduced int...
This research proposes a novel approach that utilises a crayfish optimization algorithm (COA) to adaptively optimise the wavelet filter. The COA employs correlated kurtosis (CK) as a fitness function to guide the optimization process. This method addresses limitations related to inaccurate CK period ...
This study introduces a novel hybrid optimization algorithm, the Hybrid Crayfish Optimization Algorithm with Differential Evolution (HCOADE), which addresses the limitations of premature convergence and inadequate exploitation in the traditional Crayfish Optimization Algorithm (COA). By integrating COA with ...