- 1. Automated building damage detection on digital imagery using machine learning
- (Content №6 2023)
- ... Methodology. This article presents an approach that employs a combination of unsupervised machine learning techniques, specifically Principal Component Analysis (PCA), K-means clustering, and Density-Based ...
- Created on 23 December 2023
- 2. Segmentation of heat energy consumers based on data on daily power consumption
- (Content №2 2021)
- ... Purpose. Improving the quality of the analysis of energy consumption modes of buildings of educational institutions by determining the typical patterns of their consumption by the k-means method based ...
- Created on 29 April 2021
- 3. Improved K-means algorithm automatix acquisiotion of initial clustering center
- (Information technologies, systems analysis and administration)
- ... Heilongjiang, China Abstract: Purpose. The traditional K-means algorithm requires the K value, and it is sensitive to the initial clustering center. Different initial clustering centers often ...
- Created on 23 June 2016
- 4. Ensemble classification algorithm based improved SMOTE for imbalanced data
- (Information technologies, systems analysis and administration)
- ... imbalanced data was proposed. Methodology. Firstly, the traditional SMOTE algorithm was improved to K-SMOTE (an over-sampling method based on SMOTE and K-means). In K-SMOTE, the dataset was to perform ...
- Created on 23 June 2016
- 5. A differential clustering algorithm based on elite strategy
- (Information technologies, systems analysis and administration)
- ... be used in the cluster analysis to obtain better clustering effect. Methodology. We have made in-depth research with regards to DE algorithm and cluster analysis, discussed the effect of K-means as ...
- Created on 23 June 2016
- 6. Method of Image Denoising Based on Sparse Representation and Adaptive dictionary
- (Information technologies, systems analysis and administration)
- ... which will allow removing the noises in the digital images effectively and improve the image quality. Methodology. By using K-SVD (K-means Singular Value Decomposition) algorithm, we trained the DCT ...
- Created on 23 June 2016
- 7. RBF neural networks optimization of the control over the class of stochastic nonlinear systems with unknown parameters
- (Information technologies, systems analysis and administration)
- ... are related to the objective optimization. The research investigates combinational measures of Particle Swarm Optimization (PSO) and K-means clustering. The dynamic multi-swarm particle swarm optimization ...
- Created on 02 April 2016
- 8. Dynamic multi-swarm PSO based on К-means clustering
- (Information technologies, systems analysis and administration)
- ... applications, many problems are related to the objective optimization. The research investigates combinational measures of Particle Swarm Optimization (PSO) and K-means clustering. The dynamic multi-swarm ...
- Created on 08 February 2016
- 9. Information technology of the multivariate time series fuzzy clustering on the example of the Samara river hydrochemical monitoring
- (Information technologies, systems analysis and administration)
- ... series clustering, aggregating results into a similarity matrix and determination the result fuzzy partition. Findings. Computational schemes of methods: agglomerative hierarchical, K-means, ...
- Created on 13 November 2014
- 10. Clustering algorithm based on fuzzy sets
- (To the 15th anniversary of Geoinformatic Systems Department)
- ... results of the five standard datasets clustering made by the algorithm FuzzyCluster with those made by the algorithms k-means and c-means we can see the advantages of the FuzzyCluster. Bibliography: ...
- Created on 23 November 2012