Multi objective hybridized firefly algorithm with group search optimization for data clustering

George, G. Victo Sudha; Parthiban, Latha

doi:10.1109/icrcicn.2015.7434222

Cited by 12 publications

(1 citation statement)

References 10 publications

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“…Because there are so many data, data mining is one of the most critical methods for extracting meaningful information. Data mining is a revolutionary idea utilized to tailor knowledge across numerous industries, such as medical records examination, client transaction analysis, and market surveying programs [9]. The clustering and classification algorithms are the two most essential requirements for extracting information from data mining.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Reptile Search Algorithm and Remora Optimization Algorithm for Optimization Tasks and Data Clustering

Almotairi

Abualigah

2022

Symmetry

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Data clustering is a complex data mining problem that clusters a massive amount of data objects into a predefined number of clusters; in other words, it finds symmetric and asymmetric objects. Various optimization methods have been used to solve different machine learning problems. They usually suffer from local optimal problems and unbalance between the search mechanisms. This paper proposes a novel hybrid optimization method for solving various optimization problems. The proposed method is called HRSA, which combines the original Reptile Search Algorithm (RSA) and Remora Optimization Algorithm (ROA) and handles these mechanisms’ search processes by a novel transition method. The proposed HRSA method aims to avoid the main weaknesses raised by the original methods and find better solutions. The proposed HRSA is tested on solving various complicated optimization problems—twenty-three benchmark test functions and eight data clustering problems. The obtained results illustrate that the proposed HRSA method performs significantly better than the original and comparative state-of-the-art methods. The proposed method overwhelmed all the comparative methods according to the mathematical problems. It obtained promising results in solving the clustering problems. Thus, HRSA has a remarkable efficacy when employed for various clustering problems.

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Section: Introductionmentioning

confidence: 99%