Knowledge Discovery from Dynamic Data on a Nonlinear System

A method is presented for performing knowledge discovery on the dynamic data of a nonlinear system. In the proposed approach, a synchronized phasor measurement technique is used to acquire the dynamic data of the nonlinear system and a hyper-rectangular type neural network (HRTNN) is then applied to extract crisp and fuzzy rules with which to estimate the system stability. The effectiveness of the proposed methodology is verified using the dynamic data of a typical real-world nonlinear system, namely an AEP-14 bus, and the extracted rules are relating to the knowledge discovery of the stability levels for the nonlinear system. The discovered relationships among the dynamic data (i.e., the operating state), the extracted rules, and the system stability are confirmed by means of a two-stage confirmatory factor analysis.

[1]  E. Kevin Kelloway,et al.  Structural equation modelling in perspective. , 1995 .

[2]  B. Byrne.  Factor Analytic Models: Viewing the Structure of an Assessment Instrument From Three Perspectives , 2005, Journal of personality assessment.

[3]  Engelbert Mephu Nguifo,et al.  Learning task models in ill-defined domain using an hybrid knowledge discovery framework , 2011, Knowl. Based Syst..

[4]  Philip J. Morrow,et al.  Knowledge discovery by probabilistic clustering of distributed databases , 2005, Data Knowl. Eng..

[5]  J. Rasmussen,et al.  Synchronized phasor measurements of a power system event in eastern Denmark , 2006, IEEE Transactions on Power Systems.

[6]  A. Leick.  GPS satellite surveying , 1990 .

[7]  Raymond Y. K. Lau,et al.  Knowledge discovery for adaptive negotiation agents in e-marketplaces , 2008, Decis. Support Syst..

[8]  A.G. Phadke,et al.  Synchronized phasor measurements in power systems , 1993, IEEE Computer Applications in Power.

[9]  Barbara M. Byrne,et al.  Structural equation modeling with AMOS , 2010 .

[10]  Hüseyin Gürüler,et al.  A new student performance analysing system using knowledge discovery in higher educational databases , 2010, Comput. Educ..

[11]  Sergio L. Toral Marín,et al.  Analysis of utility and use of a web-based tool for digital signal processing teaching by means of a technological acceptance model , 2007, Comput. Educ..

[12]  Patrick K. Simpson,et al.  Fuzzy min-max neural networks. I. Classification , 1992, IEEE Trans. Neural Networks.

[13]  Witold Pedrycz,et al.  Extraction of fuzzy rules from fuzzy decision trees: An axiomatic fuzzy sets (AFS) approach , 2013, Data Knowl. Eng..

[14]  Dongming Wang,et al.  Management of geometric knowledge in textbooks , 2012, Data Knowl. Eng..

[15]  Alfredo Cuzzocrea.  Advanced knowledge-based systems , 2010, Data Knowl. Eng..

[16]  Ruth Raines-Eudy,et al.  Using Structural Equation Modeling to Test for Differential Reliability and Validity: An Empirical Demonstration , 2000 .

[17]  M. Rocío Martínez-Torres,et al.  A procedure to design a structural and measurement model of Intellectual Capital: An exploratory study , 2006, Inf. Manag..

[18]  Barbara M. Byrne,et al.  Structural equation modeling with EQS : basic concepts, applications, and programming , 2000 .

[19]  G. Hancock,et al.  Performance of Bootstrapping Approaches to Model Test Statistics and Parameter Standard Error Estimation in Structural Equation Modeling , 2001 .

[20]  Mu-Chun Su.  A novel neural network approach to knowledge acquisition , 1993 .

[21]  Rex B. Kline,et al.  Principles and Practice of Structural Equation Modeling , 1998 .

[22]  P. K. Simpson.  Fuzzy Min-Max Neural Networks-Part 1 : Classification , 1992 .

[23]  Chen-Sung Chang.  A matrix-based VaR model for risk identification in power supply networks , 2011 .

[24]  Shigeo Abe,et al.  Fuzzy rules extraction directly from numerical data for function approximation , 1995, IEEE Trans. Syst. Man Cybern..

[25]  R. Moxley.  Practical Application of Synchronized Phasor Measurement , 2006, 2006 Power Systems Conference: Advanced Metering, Protection, Control, Communication, and Distributed Resources.

[26]  Amir-Masoud Eftekhari-Moghadam,et al.  Knowledge discovery in medicine: Current issue and future trend , 2014, Expert Syst. Appl..

[27]  Kit Yan Chan,et al.  A genetic algorithm based knowledge discovery system for the design of fluid dispensing processes for electronic packaging , 2009, Expert Syst. Appl..