Abstract
GRA (Grey Relational Analysis) is a typical time series similarity analysis method. However in model validation, it cannot satisfy the feature of monotonicity, and the result is lack of precision. Based on several similarity measurement criteria of time series data, traditional GRA method is developed and modified to satisfy normalization, symmetry and monotonicity. Case study shows that, improved GRA can produce a better similarity analysis result, which is in accordance with the result of TIC (Theil’s Inequality Coefficient).
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References
Mullins, J., Ling, Y., Mahadevan, S., et al.: Separation of aleatory and epistemic uncertainty in probabilistic model validation. Reliab. Eng. Syst. Saf. 147, 49–59 (2016)
Ling, Y., Mahadevan, S.: Quantitative model validation techniques: new insights. Reliab. Eng. Syst. Saf. 111, 217–231 (2013)
Jiang, X., Mahadevan, S.: Wavelet spectrum analysis approach to model validation of dynamic systems. Mech. Syst. Signal Process. 25(2), 575–590 (2011)
Liu, W., Hong, L., Qi, Z.: Model validation method of radar signal model based on spectrum estimation. Microcomput. Inf. 28(5), 161–163 (2012)
Min, F., Yang, M., Wang, Z.: Knowledge-based method for the validation of complex simulation models. Simul. Model. Pract. Theory 18(5), 500–515 (2010)
Ahn, J., Weck, O., Steele, M.: Credibility assessment of models and simulations based on NASA’s models and simulation standard using the Delphi method. Syst. Eng. 17(2), 237–248 (2014)
Crochemore, L., Perrin, C., Andreassian, V., et al.: Comparing expert judgement and numerical criteria for hydrograph evaluation. Hydrol. Sci. J. 60(3), 402–423 (2015)
Hauduc, H., Neumann, M.B., Muschalla, D., et al.: Efficiency criteria for environmental model quality assessment: a review and its application to wastewater treatment. Environ. Model. Softw. 68, 196–204 (2015)
Consonni, V., Ballabio, D., Todeschini, R.: Evaluation of model predictive ability by external validation techniques. J. Chemom. 24, 194–201 (2010)
Kheir, N.A., Holmes, W.M.: On validating simulation models of missile systems. Simulation 30(4), 117–128 (1978)
Dorobantu, A., Balas, G.J., Georgiou, T.T.: Validating aircraft models in the gap metric. J. Aircr. 51(6), 1665–1672 (2014)
Zhou, Y., Fang, K., Ma, P., Yang, M.: Complex simulation model validation method based on ensemble learning. Syst. Eng. Electron. 40(9), 2124–2130 (2018)
Wei, H., Li, Z.: Grey relational analysis and its application to the validation of computet simulation models for missile systems. Syst. Eng. Electron. 2, 55–61 (1997)
Ning, X.L., Wu, Y.X., Yu, T.P., et al.: Research on comprehensive validation of simulation models based on improved grey relational analysis. Acta Armamentarii 37(3), 338–347 (2016)
Ma, P., Zhou, Y., Shang, X., Yang, M.: Firing accuracy evaluation of electromagnetic railgun based on multicriteria optimal Latin Hypercube design. IEEE Trans. Plasma Sci. 45(7), 1503–1511 (2017)
Hundertmark, S., Lancelle, D.: A scenario for a future European shipboard railgun. IEEE Trans. Plasma Sci. 43(5), 1194–1197 (2015)
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Fang, K., Zhou, Y., Huo, J. (2019). Improved Grey Relational Analysis for Model Validation. In: Tan, G., Lehmann, A., Teo, Y., Cai, W. (eds) Methods and Applications for Modeling and Simulation of Complex Systems. AsiaSim 2019. Communications in Computer and Information Science, vol 1094. Springer, Singapore. https://doi.org/10.1007/978-981-15-1078-6_21
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DOI: https://doi.org/10.1007/978-981-15-1078-6_21
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