Gradient-based elephant herding optimization for cluster analysis

Abstract

Clustering analysis is essential for obtaining valuable information from a predetermined dataset. However, traditional clustering methods suffer from falling into local optima and an overdependence on the quality of the initial solution. Given these defects, a novel clustering method called gradient-based elephant herding optimization for cluster analysis (GBEHO) is proposed. A well-defined set of heuristics is introduced to select the initial centroids instead of selecting random initial points. Specifically, the elephant optimization algorithm (EHO) is combined with the gradient-based algorithm GBO for assigning initial cluster centers across the search space. Second, to overcome the imbalance between the original EHO exploration and exploitation, the initialized population is improved by introducing Gaussian chaos mapping. In addition, two operators, i.e., random wandering and variation operators, are set to adjust the location update strategy of the agents. Nine datasets from synthetic and real-world datasets are adopted to evaluate the effectiveness of the proposed algorithm and the other metaheuristic algorithms. The results show that the proposed algorithm ranks first among the 10 algorithms. It is also extensively compared with state-of-the-art techniques, and four evaluation criteria of accuracy rate, specificity, detection rate, and F-measure are used. The obtained results clearly indicate the excellent performance of GBEHO, while the stability is also more prominent.

Identification of the Potential Molecular Mechanism of TGFBI Gene in Persistent Atrial Fibrillation

“…In addition, we aimed to construct an AF animal model with pacemaker via persistent rapid atrial stimulation to repeat the experiment. Finally, several representative computational intelligence algorithms, like monarch butterfly optimization (MBO) [ 60 ], earthworm optimization algorithm (EWA) [ 61 ], elephant herding optimization (EHO) [ 62 ], slime mould algorithm (SMA) [ 63 ], hunger games search (HGS) [ 64 ], RUNge Kutta optimizer (RUN) [ 65 ], colony predation algorithm (CPA) [ 66 ], and Harris hawks optimization (HHO) [ 67 , 68 ] could be used to optimized our analysis.…”

Performance Enhancement of Elephant Herding Optimization Algorithm Using Modified Update Operators

“…A group of elephants live in smaller groups comprising female adult elephants and growing calves [9]. The smaller groups are called clans under the leadership of the strongest female adult elephant called the matriarch [23]. A clan moves in search of food where members' movement is influenced by the matriarch to ensure the maximum safety of the members.…”

Gradient-Based Optimizer (GBO): A Review, Theory, Variants, and Applications

“…Optimization problems [61] GBOGWO Using GBOGWO to improve the classification procedures of human activity IoT [63] GBO-kNN Proposing GBO-kNN to determine the optimal classification accuracy Feature selection [64]…”

“…In [61], the authors proposed a new hybrid method combines GBO and elephant optimization algorithm (EHO), namely, GBEHO. The main objective of GBEHO is determining the premier cluster centers at the search space.…”