英文摘要
|
Electromagnetic emissions are radiated from every part of motherboards of personal computers, and thus electromagnetic interference (EMI) occurs. EMI has a bad effect on the surrounding environment because EMI may cause malfunctions or fatal problems of other digital devices. EMI engineers diagnose EMI problems of motherboard from the electromagnetic noise data measured by the Spectrum Analyzer. It is time consuming to find out the sources (PS2, USB, VGA, etc.) of electromagnetic noise. Rough set theory (RST) is a new mathematical approach to data analysis. This paper constructs an EMI diagnostic system based on RST. There are the following steps: Data Collection, Data Preprocessing, Descretization, Attribute Reduction, Reduction Filtering, Rule Generation, Rule Filtering, Classification, and Accuracy Calculation. Historical EMI noise data, colleted from a famous motherboard company in Taiwan, are used to generate diagnostic rules. The result of our research (average diagnostic accuracy of 80%) shows that RST model is a promising approach to EMI diagnostic support system.
|
参考文献
|
-
Ahna, B. S.,Cho, S. S.,Kim, C. Y.(2000).The Integrated Methodology of Rough Set Theory and Artificial Neural Network for Business Failure Prediction.Expert Systems with Applications,18,65-74.
-
Archambeault, B.,Connor, S.(2002).IEEE International Symposium on EMC.
-
Bayardo, R. J.,Rakesh, A.,Dimitrios G.(1999).Constraint-Based Rule Mining in Large, Dense Databases.Proceeding of the 15th International Conference on Data Engineering
-
Ben-Arieh, D.,Chopra, M.,Bleyberg, M. Z.(1998).Data Mining Application for Real-time Distributed Shop Floor Control.IEEE International Conference on Systems, Man, and Cybernetics
-
Chen, F.-L.,Liu, S.-F.(2000).A Neural-Network Approach To Recognize Defect Spatial Pattern In Semiconductor Fabrication.IEEE transactions on semiconductor manufacturing,13(3),366-373.
-
Dimitras, A. I. Slowinski,R.,Susmaga, R.,Zopounidis, C.(1999).Business Failure Prediction Using Rough Sets.European Journal of Operational Research,114,263-280.
-
Gardner, R.,Bieker, J.(2000).Solving Tough Semiconductor Manufacturing Problems Using Data Mining.IEEE/SEMI Advanced Semiconductor Manufacturing Conference
-
Han, J,Kamber, M.(2001).Data Mining: Concepts and Techniques.San Francisco, CA:Morgan Kaufmann Publishers.
-
Hui, S. C.,Jha, G.(2000).Data Mining for Customer Service Support.Information &Management,38,1-13.
-
Johnson, D. S.(1974).Approximation Algorithms for Combinatorial Problems.Journal of Computer and System Sciences,9,256-278.
-
Kusiak, A.(2001).Rough Set Theory: A Data Mining Tool for Semiconductor Manufacturing.IEEE Transactions on Electronics Packaging Manufacturing,24(1),44-50.
-
Kusiak, A.(2000).Decomposition in Data Mining: An Industrial Case Study.IEEE Transactions on Electronics Packaging Manufacturing,23(4),345-353.
-
Lee, J.-H.,Yu, S.-J.,Park S.-C.(2001).IEEE transactions on semiconductor manufacturing.
-
McKee, T. E.,Lensberg, T.(2002).Genetic Programming and Rough Sets: A Hybrid Approach to Bankruptcy Classification.European Journal of Operational Research,138,436-451.
-
Mills, J. P.(1993).Electromagnetic Interference.New Jersey:Prentice Hall.
-
Morgan, D.(1994).A Handbook for EMC Testing and Measurement.London:Peter Peregrinus.
-
Pawlak, Z.(1991).Rough Sets: Theoretical Aspects of Reasoning About Data.Boston:Kluwer Academic Publishers.
-
Pawlak, Z.(1982).Rough Sets.International Journal of Information and Computer Sciences,11,341-356.
-
Pawlak, Z.,Grzymala-Busse, J. W.,Slowinski, R.,Ziarko, W.(1995).Rough Sets.Communications of the ACM,38(11),89-95.
-
Pawlak, Z.,Slowinski, R.(1994).Rough Set Approach to Multiattribute Decision Analysis.European Journal of Operational Research,72,443-459.
-
Quinlan, J. R.(1993).C4.5: Programs for Machine Learning.San Francisco, CA:Morgan Kaufmann Publishers.
-
Quinlan, J. R.(1986).Induction of Decision Trees.Machine Learning,1(1),81-106.
-
Skinner, K. R.,Montgomery, D. C.,Runger, G. C.,Fowler, J. W.,McCarville, D. R.,Rhoads, T. R.,Stanley, J. D.(2002).Multivariate Statistical Methods for Modeling and Analysis of Wafer Probe Test Data.IEEE transactions on semiconductor manufacturing,15(4),523-530.
-
Slowinski, R.,Stefanowski, J.(1994).New Approaches in Classification and Data Analysis.Berlin:Springer.
-
Sushmita, M.,Sankar, K. P.,Pabitra, M.(2002).Data Mining in Soft Computing Framework: A Survey.IEEE Transactions on Neural Networks,13(1),3-14.
-
Vinterbo, S.,Øhrn, A.(2000).Minimal Approximate Hitting Sets and Rule Templates.International Journal of Approximate Reasoning,25(2),123-143.
-
Walczak, B.,Massart, D. L.(1999).Rough Set Theory.Chemometrics and Intelligent Laboratory Systems,47,1-16.
-
Yoshida, T.,Touzaki, H.(1999).A Study on Association Among Dispatching Rules in Manufacturing Scheduling Problems.IEEE International Conference on Emerging Technologies and Factory Automation,2,1355-1360.
-
簡禎富、林鼎浩、彭誠湧、徐紹鐘(2001)。建構半導體晶圓允收測試資料挖礦架構及其實證研究。工業工程學刊,18(4),37-48。
|