Author:
Rozhnov I,Kazakovtsev L,Bezhitskaya E,Bezhitskiy S
Abstract
Abstract
This paper focuses on new proposed algorithms for cluster problem solving. The proposed algorithms are based on Classification EM algorithm (CM-algorithm). The algorithms are new algorithms of the greedy heuristic method using the idea of searching in alternating neighborhoods. The numerical experiments show that the proposed algorithms have less mean values and/or less standard deviation of objective function, less scatter of obtained values in comparison with classical CEM-algorithm.
Reference10 articles.
1. EM-algorithm, its modications and their application to the problem of separation of mixtures of probability distributions;Korolev,2007
2. Overview of basic data classification and clustering methods;Cherezov;Bulletin “System Analysis and Information Technologies “,2009
3. The choice of a metric for a system for the automatic classification of radio products by production batches;Kazakovtsev;Software products and systems,2015
4. Improved model for detection of homogeneous production batches of electronic components;Kazakovtsev;IOP Conference Series: Materials Science and Engineering,2017
5. Algorithms with Greedy Heuristic Procedures for Mixture Probability Distribution Separation;Kazakovtsev;Yugoslav Journal of Operations Research,2019
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献