A sampling-pso-k-means algorithm for document clustering. KAMEL N,OUCHEN I,BAALI K. . 2014Nadjet Kamel, Imane Ouchen, Karim Baali, "A Sampling PSOKmeans Algorithm for Document Clustering", Advances in Intelligen
The K-means algorithm is a basic and most widely used division method among clustering analysis methods. It is a method of discovering clusters and cluster centers in unclassified labeled data [9]. Its main advantage is that the algorithm is simple and fast. If the resulting clusters are dense...
method of Technical Analysis, K-means clustering algorithm, and Mean-Variance portfolio optimization model was proposed in this paper. The study aims to integrate these three important analyses to come up with the best portfolio. This paper uses the average annual risk and an annual rate of retur...
K-means clusteringis a robust unsupervised clustering method. K-means algorithm uses the criteria of squared error, likeEuclidean distancemeasure, for calculating the distance between the data points for the process of grouping. K-means follows the typical process of clustering with first initializing ...
This study presents the K-means clustering-based grey wolf optimizer, a new algorithm intended to improve the optimization capabilities of the conventional grey wolf optimizer in order to address the problem of data clustering. The process that groups similar items within a dataset into non-overlappi...
Overview of the proposed hybrid oil price prediction model. This flowchart illustrates the three-phase training process: initial training of the DSD-LSTM model, application of the K-means algorithm to form clusters within the data, and subsequent fine-tuning of duplicated DSD-LSTM models for each...
means algorithm, and the cluster centers become the new training samples. This step streamlines the complexity and enhances the algorithm’s performance. Each training sample is weighted according to the size of its cluster, favoring larger clusters for improved accuracy. The revised dataset ...
引用格式: 周旭涛,赵海旭,蒋玉峰,等.基于 K-means聚类粒子群算法的海洋结构迭代型损伤识别方法[J].中国海洋 大学学报(自然科学版),2025,55(4):134-147.ZhouXutao,Zhao Haixu,JiangYufeng,etal.Iterativedamageidentification methodforoffshorestructuresbasedon K-meansclusteringparticleswarmalgorithm[J].Periodicalof...
To address the drawbacks of the traditional k-means algorithm for mineral mapping, CKM provides three improvements: a modified similarity measurement method, enhanced spectral absorption features, and combined mineral mapping results as K is incremented. Fig. 4 shows a flowchart for the CKM procedure...
SVM machine learning GLCM algorithm K-means clustering LBP 1. Introduction Agriculture is an essential core sector that provides livelihood to the world population. Most of the population depends on agricultural crop production. Almost 75% of people are getting life resources from agriculture, but at...