Fuzzy Method of Revealing Implicit Causality within a Control System

被引：0

作者：

Nazarov, Dmitry M. ^{[1
]}

Begicheva, Svetlana V. ^{[1
]}

Azarov, Dmitry A. ^{[1
]}

机构：

[1] Ural State Univ Econ, Business Informat Sci Dept, Ekaterinburg, Russia

来源：

2016 IEEE 10TH INTERNATIONAL CONFERENCE ON APPLICATION OF INFORMATION AND COMMUNICATION TECHNOLOGIES (AICT) | 2016年

关键词：

Causality; control system; data mining; fuzzy model; implicit factor; LOGIC;

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：

The article addresses the problem of identifying subtle causal relations between sets of data defining a control system. The key pros and cons of using a fuzzy method are later examined. It explains the primary aspects of the fuzzy model for revealing implicit causality within a control system based on a combination of a fuzzy set approach and data mining techniques. The tool for carrying out evaluation in natural language resulting from utilizing an automated learning algorithm is advanced afterwards. The paper lastly proves its applicability to modeling mutual effects of a number of economic objects on each other.

引用

页码：182 / 186

页数：5

共 18 条

[1]

Azarov D. A., 2015, P BI TECHN OPT BUS P, P35

[2] Shaping the Next Incarnation of Business Intelligence Towards a Flexibly Governed Network of Information Integration and Analysis Capabilities [J].

Baars, Henning ;

Felden, Carsten ;

Gluchowski, Peter ;

Hilbert, Andreas ;

Kemper, Hans-Georg ;

Olbrich, Sebastian .

BUSINESS & INFORMATION SYSTEMS ENGINEERING, 2014, 6 (01) :11-16

[3]

Bellman R.E, 2015, Adaptive control processes: a guided tour

[4]

Cybenko G., 1989, Mathematics of Control, Signals, and Systems, V2, P303, DOI 10.1007/BF02551274

[5]

De Reus N.M, 1994, FEL93A158 TNO PHYS E

[6] LOGIC OF INEXACT CONCEPTS [J].

GOGUEN, JA .

SYNTHESE, 1969, 19 (3-4) :325-373

[7] CAUSALITY, COINTEGRATION, AND CONTROL [J].

GRANGER, CWJ .

JOURNAL OF ECONOMIC DYNAMICS & CONTROL, 1988, 12 (2-3) :551-559

[8]

Kharitonov V. A., 2012, MANAGEMENT EC SYSTEM, P7

[9] FUZZY-SYSTEMS AS UNIVERSAL APPROXIMATORS [J].

KOSKO, B .

IEEE TRANSACTIONS ON COMPUTERS, 1994, 43 (11) :1329-1333

[10]

Kruglov V.V., 2001, Fuzzy logic and artificial neural networks

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