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Study on Color Spectrum Prediction Accuracy of CYNSN Model

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Abstract:

Based on comparison of spectrum models, this paper chose CYNSN spectrum model as the study object, spectrum prediction as the main study content, the best model parameters’ acquisition as the aim, RRMS and GFC as the evaluate parameters of prediction accuracy. This paper designed the experiment, training samples and test samples to measure and calculate the parameters by programming: Ai (effective dot coverage ratio of the i-th Neugebauer primary), Rλ, i (spectral reflectivity of the i-th Neugebauer primary), n (Yule-Nielsen coefficient) and cell (cell number). The result of experiment and calculation shows that the best n value is 2.8 and cell number is 6. The result of CYNSN Model’s Color Spectrum prediction Accuracy shows that the average RMS is 0.0002, the max RRMS is only 0.0005, the GFC value is approximately 1, that is to say the CYNSN model achieved the better spectrum prediction accuracy after setting the best value of parameter.

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Periodical:

Applied Mechanics and Materials (Volume 262)

Pages:

3-8

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.262.3

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Online since:

December 2012

Authors:

Zhan Jun Si, Yuan Hu, Jia Wang, Yu Li

Keywords:

Cell Number, CYNSN Model, RRMS, Rλ, Spectrum

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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References

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Google Scholar