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1
Optimized clustering with modified K-means algorithm
Published 2021“…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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2
A near-optimal centroids initialization in K-means algorithm using bees algorithm
Published 2009“…The K-mean algorithm is one of the popular clustering techniques.The algorithm requires user to state and initialize centroid values of each group in advance. …”
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3
Determining optimal location of static VAR compensator by means of genetic algorithm
Published 2011“…The purpose of this paper is to study a practical and accurate heuristic method known as genetic algorithm (GA) which is used to find the optimal location of Static Var Compensator (SVC) and its appropriate size and setting. …”
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4
Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…These algorithms mostly built upon the partitioning k-means clustering algorithm. …”
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5
Clustering chemical data set using particle swarm optimization based algorithm
Published 2008“…In this study, Particle Swarm Optimization (PSO) based clustering algorithm is exploited to optimize the results of other clustering algorithm such as K-means. …”
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6
An improved artificial bee colony algorithm based on mean best-guided approach for continuous optimization problems and real brain MRI images segmentation
Published 2024“…The artificial bee colony (ABC) algorithm is a relatively new algorithm inspired by nature and has been shown to be efficient in contrast to other optimization algorithms. …”
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7
RSA Encryption & Decryption using JAVA
Published 2006“…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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8
Optimization of modified Bouc–Wen model for magnetorheological damper using modified cuckoo search algorithm
Published 2021“…The final value of the fitness function and the iteration number it took to converge were used as the qualifying indicator to the proposed cuckoo search algorithm efficiency. A comparison was done against particle swarm optimization, genetic algorithm, and sine–cosine algorithm, where the modified cuckoo search algorithm showed the lowest root mean square error and fastest convergence rate among the three algorithms.…”
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9
Elitism Based Migrating Birds Optimization Algorithm for Optimization Testing
Published 2017“…Migrating Birds Optimization Algorithm (MBO) has gained popularity in solving various engineering problems because it yielded a good and consistent result. …”
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10
A Comparative Study on three Component Selection Mechanisms for Hyper-Heuristics in Expensive Optimization
Published 2018“…The performance of hyper-heuristics is highly encouraging against a specifically tailored algorithm for CEC test set of expensive optimization problems.…”
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11
Data clustering using the bees algorithm
Published 2007“…K-means clustering involves search and optimization. …”
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12
Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems
Published 2023“…SGD uses random or batch data sets to compute gradient in solving optimization problems. …”
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13
Modeling and Analysis of New Hybrid Clustering Technique for Vehicular Ad Hoc Network
Published 2023“…To address these problems, a novel method combining a covering rough set and a K-Means clustering algorithm (RK-Means) was proposed in this paper. …”
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14
Optimization Of Pid Controller For Double-Link Flexible Robotic Manipulator Using Metaheuristic Algorithms
Published 2019“…This signifies that, the PSO and ABC algorithm are very effective in optimizing the PID parameters.…”
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Proceeding -
15
Discovering optimal clusters using firefly algorithm
Published 2016“…Existing conventional clustering techniques require a pre-determined number of clusters, unluckily; missing information about real world problem makes it a hard challenge.A new orientation in data clustering is to automatically cluster a given set of items by identifying the appropriate number of clusters and the optimal centre for each cluster.In this paper, we present the WFA_selection algorithm that originates from weight-based firefly algorithm.The newly proposed WFA_selection merges selected clusters in order to produce a better quality of clusters.Experiments utilising the WFA and WFA_selection algorithms were conducted on the 20Newsgroups and Reuters-21578 benchmark dataset and the output were compared against bisect K-means and general stochastic clustering method (GSCM).Results demonstrate that the WFA_selection generates a more robust and compact clusters as compared to the WFA, bisect K-means and GSCM.…”
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16
Integrating genetic algorithms and fuzzy c-means for anomaly detection
Published 2005“…Traditional anomaly detection algorithms require a set of purely normal data from which they train their model. …”
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17
Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri
Published 2020“…In this research, the empirical experiments have been conducted for the five selected algorithms in the engineering optimization discipline, namely Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Ant Colony Optimization (ACO) and Artificial Immune System (AIS). …”
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18
Multichannel optimization with hybrid spectral- entropy markers for gender identification enhancement of emotional-based EEGs
Published 2021“…Consequently, optimization algorithms including binary gravitation search algorithm (BGSA) and binary particle swarm optimization (BPSO), were employed to identify the optimal channels for gender classification. …”
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19
Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application
Published 2020“…Performance Testing is used to test the performance of algorithm implementations in applications. …”
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20
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The first research objective is to develop a new deep learning algorithm by a hybrid of DNN and K-Means Clustering algorithms for estimating the Lorenz chaotic system. …”
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