A Memetic Fuzzy Whale Optimization Algorithm for Data Clustering

Wu, Ze-Xue; Huang, Ko-Wei; Chen, Jui-Le; Yang, Chu-Sing

doi:10.1109/cec.2019.8790044

Cited by 8 publications

(8 citation statements)

References 22 publications

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“…This is to ensure that all the whales stay close to the prey. Consider the following [102] , [103] :

Where

is the current position of the

whale and D is the number of search space dimensions. The position of the whales at the next sampling instant can be updated using three methods.…”

Section: A Review Of Various Swarm-based Motmentioning

confidence: 99%

“…The position of the whales at the next sampling instant can be updated using three methods. The first method is via a random search and is shown as [99] , [102] , [103] :

1

Where

is the position of a whale chosen at random and A and C are coefficients. A is based on the current and maximum iteration numbers, as well as a random number in the range [

01

].…”

Section: A Review Of Various Swarm-based Motmentioning

confidence: 99%

“…Bubble net attacking is a mathematical model used to imitate the spiral movement of the humpback whale [67] , [68] . In bubble net attacking, the whales update their positions as follows [99] , [102] , [103] :

1

Where b is a limited constant and l is a random number in the range [

11

]. The method of position updating to be used is based on a random number q in the range [

01

], as well as the value of A .…”

Section: A Review Of Various Swarm-based Motmentioning

confidence: 99%

See 2 more Smart Citations

A review of swarm-based metaheuristic optimization techniques and their application to doubly fed induction generator

Reddy

Saha

2022

Heliyon

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“…This is to ensure that all the whales stay close to the prey. Consider the following [102] , [103] :

Where

is the current position of the

whale and D is the number of search space dimensions. The position of the whales at the next sampling instant can be updated using three methods.…”

Section: A Review Of Various Swarm-based Motmentioning

confidence: 99%

“…The position of the whales at the next sampling instant can be updated using three methods. The first method is via a random search and is shown as [99] , [102] , [103] :

1

Where

is the position of a whale chosen at random and A and C are coefficients. A is based on the current and maximum iteration numbers, as well as a random number in the range [

01

].…”

Section: A Review Of Various Swarm-based Motmentioning

confidence: 99%

1

Where b is a limited constant and l is a random number in the range [

11

]. The method of position updating to be used is based on a random number q in the range [

01

], as well as the value of A .…”

Section: A Review Of Various Swarm-based Motmentioning

confidence: 99%

See 1 more Smart Citation

A review of swarm-based metaheuristic optimization techniques and their application to doubly fed induction generator

Reddy

Saha

2022

Heliyon

View full text Add to dashboard Cite

“…Sheikhi (2021) proposed a fake news detection system based on content features and the WOA-Xgbtree algorithm, which had achieved good results in news classification. Wu et al (2019) proposed a memetic fuzzy whale optimization (MFWO) algorithm to solve the data clustering problem. Samantaray and Sahoo (2021) designed a hybrid model combining a support vector machine and whale optimization algorithm (SVM-WOA), which more effectively predicted suspended sediment concentration than the SVM-PSO model.…”

Section: Introductionmentioning

confidence: 99%

Association Rule Mining Based on Hybrid Whale Optimization Algorithm

Cai

Wang

et al. 2022

International Journal of Data Warehousing and Mining

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Association Rule Mining(ARM) is one of the most significant and active research areas in data mining. Recently, Whale Optimization Algorithm (WOA) has been successfully applied in the field of data mining, however, it easily falls into the local optimum. Therefore, an improved WOA based adaptive parameter strategy and Levy Flight mechanism (LWOA) is applied to mine association rules. Meanwhile, a hybrid strategy that blends two algorithms to balance the exploration and exploitation phases is put forward, that is, grey wolf optimization algorithm (GWO), artificial bee colony algorithm (ABC) and cuckoo search algorithm (CS) are devoted to improving the convergence of LWOA. The approach performs a global search and finds the association rules sets by modeling the rule mining task as a multi-objective problem that simultaneously meets support, confidence, lift, and certain factor, which is examined on multiple data sets. Experimental results verify that the proposed method has better mining performance compared to other algorithms involved in the paper.

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“…A clustering algorithm based on a modified WOA is proposed in Majhi (2019) for solving automobile insurance fraud detection. Wu et al (2019) combined the fuzzy C-means algorithm with a WOA for solving data clustering problems. Authors have proved the effectiveness of their hybrid approach using eight benchmark datasets.…”

Section: Introductionmentioning

confidence: 99%

A novel data clustering approach based on whale optimization algorithm

Singh

2020

Expert Systems

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Data clustering is an important technique of data mining in which the objective is to partition N data objects into K clusters that minimize the sum of intra‐cluster distances between each data object to its nearest centroid. This is an optimization problem, and various optimization algorithms have been suggested for capturing the position vectors of optimal centroids. However, in these approaches, the problem of local entrapment is very common due to weak exploration mechanism. In this paper, a novel approach based on a whale optimization algorithm (WOA) is suggested for data clustering. The performance of the suggested approach is validated using 14 benchmark datasets of the UCI machine learning repository. The experimental results and various statistical tests have justified the efficacy of the suggested approach.

show abstract

A Memetic Fuzzy Whale Optimization Algorithm for Data Clustering

Cited by 8 publications

References 22 publications

A review of swarm-based metaheuristic optimization techniques and their application to doubly fed induction generator

A review of swarm-based metaheuristic optimization techniques and their application to doubly fed induction generator

Association Rule Mining Based on Hybrid Whale Optimization Algorithm

A novel data clustering approach based on whale optimization algorithm

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