scholarly journals Information Technology for Classification of Donosological and Pathological States Using the Ensemble of Data Mining Methods

2021 ◽  
Vol 2021 (1(203)) ◽  
pp. 77-94
Author(s):  
O. KRYVOVA ◽  
L. KOZAK
2016 ◽  
Vol 51 (20) ◽  
pp. 2853-2862 ◽  
Author(s):  
Serkan Ballı

The aim of this study is to diagnose and classify the failure modes for two serial fastened sandwich composite plates using data mining techniques. The composite material used in the study was manufactured using glass fiber reinforced layer and aluminum sheets. Obtained results of previous experimental study for sandwich composite plates, which were mechanically fastened with two serial pins or bolts were used for classification of failure modes. Furthermore, experimental data from previous study consists of different geometrical parameters for various applied preload moments as 0 (pinned), 2, 3, 4, and 5 Nm (bolted). In this study, data mining methods were applied by using these geometrical parameters and pinned/bolted joint configurations. Therefore, three geometrical parameters and 100 test data were used for classification by utilizing support vector machine, Naive Bayes, K-Nearest Neighbors, Logistic Regression, and Random Forest methods. According to experiments, Random Forest method achieved better results than others and it was appropriate for diagnosing and classification of the failure modes. Performances of all data mining methods used were discussed in terms of accuracy and error ratios.


Author(s):  
YONG SHI

On behalf of the editorial advisory board of the International Journal of Information Technology and Decision Making (IT&DM), the Editor-in-Chief reviews the current research trend of this journal based on all the papers published in 2008. They are web-based decision analysis, credit scoring techniques and new data mining methods which combine both decision-making techniques and information technology tools. In addition, the Editor-in-Chief summarizes the key ideas of contributions in this new issue that may contain new research trend of IT&DM in 2009.


2011 ◽  
Vol 44 (2) ◽  
pp. e39-e40
Author(s):  
Maik Götze ◽  
Christian Wolff ◽  
Bernd Krause ◽  
Dietrich Romberg

2014 ◽  
Vol 687-691 ◽  
pp. 1266-1269
Author(s):  
Zhen Wang ◽  
Kan Kan She

With the rapid development of information technology, the amount of data accumulated by people is increasing sharply. Data mining technology is an effective method to find useful information from vast amounts of data and increase the utilization of information. After thousands of years of development, traditional Chinese medicine has accumulated a wealth of theoretical knowledge and a lot of books and records, more and more Chinese medicine databases are created. Using data mining technology to mine the unknown knowledge and rules and put forward assumptions for experiment and theory can be a good auxiliary research of traditional Chinese medicine. This article analyzes the data mining methods of traditional Chinese medicine at first. Then, the application of data mining technology in traditional Chinese medicine data analysis is introduced which includes the data mining of traditional Chinese medicine literatures, diagnosis and clinic of traditional Chinese medicine and prescription and medication of traditional Chinese medicine. At last, the aspects which need to be paid attention to in the data mining of traditional Chinese medicine are pointed out.


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