On Multivariate Method of Qualitative Analysis of Hodgkin-Huxley Model with Decision Tree Induction

被引：0

作者：

Martsenyuk, Vasyl ^{[1
]}

Warwas, Kornel ^{[1
]}

Augustynek, Krzysztof ^{[1
]}

Klos-Witkowska, Aleksandra ^{[1
]}

Karpinskyi, Volodymyr ^{[2
]}

Klymuk, Natalya ^{[3
]}

Mayhruk, Zoryana ^{[3
]}

机构：

[1] Univ Bielsko Biala, Dept Comp Sci & Automat, Willowa 2, Bielsko Biala, Poland

[2] Coventry Univ, TechnoCtr, Scanners UK Ltd 3D, Coventry, W Midlands, England

[3] Ternopil State Med Univ, Voli Sq 1, UA-46001 Ternopol, Ternopilska Obl, Ukraine

来源：

2016 16TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS (ICCAS) | 2016年

关键词：

cell excitability; Hodgkin-Huxley model; qualitative analysis; decision tree induction; data mining; NEURAL EXCITABILITY;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents a data mining technique for qualitative analysis of Hodgkin-Huxley model of cell excitability. Such problem cannot be solved analytically. Therefore we apply Monte-Carlo techniques for the generation of model parameters, and use data mining algorithm for classification of learning tuples obtained. As a result we attain a decision tree capable of classifying the excitability depending on the relationship between initial conditions and between rate constants. Details of software development and issues of computational complexity are presented. The software includes the package of Java-classes. An example for classification of excitability of three types is presented

引用

页码：489 / 494

页数：6

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