PSO+K-means Algorithm for Anomaly Detection in Big Data

Alguliyev, Rasim; Alıguliyev, Ramiz M.; Abdullayeva, Fargana J.

doi:10.19139/soic.v7i2.623

Cited by 17 publications

(15 citation statements)

References 18 publications

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“…In order to prove the effectiveness of the method proposed here, we compared it to two other methods: the Black Hole Optimization (BHO), recently proposed in [15], and Particle Swarm Optimization (PSO) [17]. Remarkably, such two methods, as well as the one proposed in this work, adopt a master-slave methodology to solve OPF problems.…”

Section: Methods Used For Comparisonmentioning

confidence: 99%

Optimal Power Flow in Direct Current Networks Using the Antlion Optimizer

Rivera¹,

Ocampo²,

Grisales-Noreña³

et al. 2020

Stat., optim. inf. comput.

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This document presents a solution method for optimal power flow (OPF) problem in direct current (DC) networks by implementing a master-slave optimization methodology that combines an antlion optimizer (ALO) and a power flow approach based on successive approximation (SA ). In the master stage, the ALO determines the optimal amount of power to be delivered by all the distributed generators (DGs) in order to minimize the total power losses in the distribution lines of the DC network. In slave stage, the power flow problem is solved considering constant power loads and power outputs of DGs as constants. To validate the effectiveness and robustness of the proposed model, two additional comparative methods were implemented: particle swarm optimization (PSO) and black hole optimization (BHO). Two distribution test feeders (21 and 69 nodes) were simulated under different scenarios of distributed power generation. The simulations, conducted in MATLAB 2018$b$, show that the proposed method (ALO) presents a better balance between power loss minimization and computational time required to find the optimal solution regardless of the size of the DC network.

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Section: Methods Used For Comparisonmentioning

confidence: 99%

Optimal Power Flow in Direct Current Networks Using the Antlion Optimizer

Rivera¹,

Ocampo²,

Grisales-Noreña³

et al. 2020

Stat., optim. inf. comput.

View full text Add to dashboard Cite

show abstract

“…Instead of randomly choosing the initial centroid value, the centroid values are calculated with an additional step to divide between the minimal and the maximal intra-cluster distance in [28]. In another study, Alguliyev et al [29] performed particle swarm optimization (PSO) to the data after applying k-means clustering. The PSO will group the data objects based on the minimum distance criterion and evaluate the fitness function.…”

Section: Partition-based Clusteringmentioning

confidence: 99%

A Review on Clustering Techniques: Creating Better User Experience for Online Roadshow

2021

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Online roadshow is a relatively new concept that has higher flexibility and scalability compared to the physical roadshow. This is because online roadshow is accessible through digital devices anywhere and anytime. In a physical roadshow, organizations can measure the effectiveness of the roadshow by interacting with the customers. However, organizations cannot monitor the effectiveness of the online roadshow by using the same method. A good user experience is important to increase the advertising effects on the online roadshow website. In web usage mining, clustering can discover user access patterns from the weblog. By applying a clustering technique, the online roadshow website can be further improved to provide a better user experience. This paper presents a review of clustering techniques used in web usage mining, namely the partition-based, hierarchical, density-based, and fuzzy clustering techniques. These clustering techniques are analyzed from three perspectives: their similarity measures, the evaluation metrics used to determine the optimality of the clusters, and the functional purpose of applying the techniques to improve the user experience of the website. By applying clustering techniques in different stages of the user activities in the online roadshow website, the advertising effectiveness of the website can be enhanced in terms of its affordance, flow, and interactivity.

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“…Correspondingly, the literature on Pareto optimization methods for decision-making very extensive and we can indicate here only an insignificant number of theoretical and applied works: see e.g. ( [1] [2] [3] [4] [5] [6] [7] ).…”

Section: Introductionmentioning

confidence: 99%

Applications of Some Rating Methods to Solve Multicriteria Decision-Making Problems

Gogodze¹

2020

Stat., optim. inf. comput.

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This study proposes a new approach for the solution of multicriteria decision-making problems. The proposed approach is based on using rating/ranking methods. Particularly, in this paper, we investigate the possibility of applying Massey, Colley, Keener, offence-defence, and authority-hub rating methods, which are successfully used in various fields. The proposed approach is useful when no decision-making authority is available or when the relative importance of various criteria has not been previously evaluated. The proposed approach is tested with an example problem to demonstrate its viability and suitability for application.

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PSO+K-means Algorithm for Anomaly Detection in Big Data

Cited by 17 publications

References 18 publications

Optimal Power Flow in Direct Current Networks Using the Antlion Optimizer

Optimal Power Flow in Direct Current Networks Using the Antlion Optimizer

A Review on Clustering Techniques: Creating Better User Experience for Online Roadshow

Applications of Some Rating Methods to Solve Multicriteria Decision-Making Problems

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