Reserch on a NOx Emission Forecasting Method Based on Naïve Bayesian

Zhang Lin; Wang Xin; Zhang Qi

doi:10.4028/www.scientific.net/AMR.936.1857

Paper Titles

Comparisons of Explicit and Implicit Finite Element Methods for Sheet Metal Forming
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Numerical Simulation Study of the Influence of Turning Depth on the Bending Vibration Mode of Work-Piece
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Application of Multidisciplinary Design Optimization in the Casting Process Optimization
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Analysis of the Common Causes of Papermaking Cast Iron Dryer's Defects and the Study of Test On-Line
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Analysis of Grinding Roller Stress Distribution of Vertical Roller Mill
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Establish the Load Distribution Model for Vertical Mill Grinding Roller in Width Direction
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The Optimal Levenberg-Marquardt Algorithm to Predict Welding Quality Using Mahalanobis Distance Theory
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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 936Reserch on a NOx Emission Forecasting Method Based...

Reserch on a NO_x Emission Forecasting Method Based on Naïve Bayesian

Abstract:

Increasingly serious environmental pollution,trying to find a effective method to control NOx emission become more importance. Under this background, this paper adopts the naïve Bayesian classifier method which built on the basis of the probability density function to forecasting the NOx emission of diesel engine. This paper proposes a new approach to weight the super-parent one dependence estimators, and uses the UCI datasets to verify the validity of the proposed method. Finally, apply this diagnosis technology to the collected WD615 diesel engine data. The comparison experiments with other algorithms demonstrate the effectiveness of the proposed method.

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Periodical:

Advanced Materials Research (Volume 936)

Pages:

1857-1861

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.936.1857

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Online since:

June 2014

Authors:

Zhang Lin*, Wang Xin, Zhang Qi

Keywords:

Diesel Engine, Naïve Bayesian Classifier, NO_x, One-Dependence Classifier

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References

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