Then we obtained a novel hybrid algorithm, the Grey Wolf Optimizer algorithm optimized backpropagation neural networks algorithm (GNNA), designed for predicting species' potential distribution. We also compared
This work proposes a new meta-heuristic called Grey Wolf Optimizer (GWO) inspired by grey wolves (Canis lupus). The GWO algorithm mimics the leadership hierarchy and hunting mechanism of grey wolves in nature. Four types of grey wolves such as alpha, beta, delta, and omega are employed for...
class GreyWolfOptimizer: def __init__(self, alpha_pos, beta_pos, delta_pos, wolf_count, dim, max_iter): self.alpha_pos = np.array(alpha_pos) self.beta_pos = np.array(beta_pos) self.delta_pos = np.array(delta_pos) self.wolf_count = wolf_count self.dim = dim self.max_iter ...
In the first part, the proposed algorithm is analyzed through rigorous experiments on different classes of test functions of the Congress on Evolutionary Computation benchmark 2014 using Friedman statistical test, among them, comparing the original grey wolf optimizer algorithm, it achieved better ...
灰狼优化算法是一种启发式优化技术，旨在模拟自然界中灰狼的集体行为，以解决复杂的优化问题。其主要特点和优势如下：核心理念：将搜索空间中的各个解视为灰狼群体中的个体。Alpha、Beta和Delta分别代表最优解、次优解和第三优解。Omega则根据Alpha、Beta和Delta的指示进行探索。搜索机制：通过追踪、包围和...
1. 算法流程(continuous gray wolf optimization (CGWO) algorithm.) 2. 基于GWO的特征选择算法 2.1 算法1(bGWO1) 2.2 算法2 bGWO2) 2.3 特征选择算法 1) Fitness=α∗γR(D)+β∗|C−R||C| 其中γR(D) 是在部分特征集 R的分类质量 , C 全部特征集, α∈[0,1],β=1−α。 2) Fit...
In this paper, application of evolutionary intelligence-based Grey Wolf Optimizer (GWO) algorithm has been presented to estimate the optimal parameters of Proportional-Integral-Derivative (PID) controller for load frequency control(LFC) in multi-source single area power network. The multi-source single...
灰狼算法（Grey Wolf Optimizer, GWO）是一种启发式优化技术，旨在模拟自然界中灰狼的集体行为，以解决复杂的优化问题。算法的核心理念是将搜索空间中的各个解视为灰狼群体中的个体，其中Alpha、Beta和Delta分别代表最优解、次优解和第三优解，而Omega则根据Alpha、Beta和Delta的指示进行探索。灰狼算法通过...
concepts and the formulation of the fitness function for the same problem. Section "Proposed K-means clustering grey wolf optimizer" comprehensively presents the formulation of the proposed KCGWO based on the \(K\)-means clustering algorithm; in addition, the basic concepts of GWO are also ...
灰狼优化算法（Grey Wolf Optimizer, GWO）是一种基于自然界灰狼行为的高效优化工具，它模仿了灰狼的社会结构和狩猎策略。算法的核心在于模拟狼群中的Alpha、Beta、Delta和Omega角色，其中Alpha代表最优解，其他角色协同寻找解决方案。GWO通过追踪、包围和攻击的方式，在多变量和多目标问题中展现了强大的全局...