[1] Ding Weiming, Wu Xiaoli, Wei Haikun,. Prediction of coal ash fusion temperatureusing constructive-pruning hybrid method for RBF networks [J]. Journal of Southeast University (English Edition), 2011, 27 (2): 159-163. [doi:10.3969/j.issn.1003-7985.2011.02.009]

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Prediction of coal ash fusion temperatureusing constructive-pruning hybrid method for RBF networks()

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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

27

Issue:

2011 2

Page:

159-163

Research Field:

Chemistry and Chemical Engineering

Publishing date:

2011-06-30

Info

Title:

Prediction of coal ash fusion temperatureusing constructive-pruning hybrid method for RBF networks

Author(s):

Ding Weiming¹;  Wu Xiaoli¹;  Wei Haikun²

¹ School of Energy and Environment, Southeast University, Nanjing 210096, China
² School of Automation, Southeast University, Nanjing 210096, China

Keywords:

radial basis function(RBF)networks;  function approximation;  ash fusion temperature

PACS:

TQ520.62

DOI:

10.3969/j.issn.1003-7985.2011.02.009

Abstract:

A constructive-pruning hybrid method(CPHM)for radial basis function(RBF)networks is proposed to improve the prediction accuracy of ash fusion temperatures(AFT). The CPHM incorporates the advantages of the construction algorithm and the pruning algorithm of neural networks, and the training process of the CPHM is divided into two stages: rough tuning and fine tuning. In rough tuning, new hidden units are added to the current network until some performance index is satisfied. In fine tuning, the network structure and the model parameters are further adjusted. And, based on components of coal ash, a model using the CPHM is established to predict the AFT. The results show that the CPHM prediction model is characterized by its high precision, compact network structure, as well as strong generalization ability and robustness.

References:

[1] van Dyk J C, Keyser M J, van Zyl J W. Suitability of feedstocks for the Sasol-Lurgi fixed bed dry bottom gasification process[C]//Gasification Technologies Conference. San Francisco, USA, 2001:1-11.
[2] Romero C E, Saro R D, Craparo J, et al. Laser-induced breakdown spectroscopy for coal characterization and assessing slagging propensity[J]. Energy Fuels, 2010, 24(1): 510-517.
[3] Song W J, Tang L H, Zhu X D, et al. Effect of coal ash composition on ash fusion temperatures [J]. Energy Fuels, 2010, 24(1):182-189.
[4] Dunnu G, Maier J, Scheffknecht G. Ash fusibility and compositional data of solid recovered fuels[J]. Fuel, 2010, 89(7):1534-1540.
[5] Kalogirou S A. Artificial intelligence for the modeling and control of combustion processes[J]. Progress in Energy and Combustion Seience, 2003, 29(6): 515-566.
[6] Amoudi A, Zhang L. Application of radial basis function networks for solar array modeling and maximum power-point prediction[J]. IEE Proceedings: Generation, Transmission and Distribution, 2000, 147(5): 310-316.
[7] Chandok J S, Kar I N, Tuli Suneet. Estimation of furnace exit gas temperature(FEGT)using optimized radial basis and back-propagation neural networks[J]. Energy Conversion and Management, 2008, 49(8):1989-1998.
[8] Orr M. Regularization in the selection of radial basis function centers[J]. Neural Computation, 1995, 7(3):606-623.
[9] Plat J. A resource-allocating network for function interpolation[J]. Neural Computation, 1991, 3(2):213-225.
[10] Chen S. Local regularization assisted orthogonal least squares regression[J]. Neurocomputing, 2006, 69(4/5/6):559-585.
[11] Weigend A, Rumelhart D, Huberman B. Generalization by weight-elimination with application to forecasting[C]//Advances in Neural Information Processing Systems. Cambridge, MA, USA: The MIT Press, 1991, 3: 875-882.

Memo

Memo:

Biography: Ding Weiming(1959—), male, associate professor, wmding@seu.edu.cn.
Foundation items: The National Natural Science Foundation of China(No. 60875035), the Natural Science Foundation of Jiangsu Province(No.BK2008294), the National High Technology Research and Development Program of China(863 Program)(No.2006AA05A107).
Citation: Ding Weiming, Wu Xiaoli, Wei Haikun. Prediction of coal ash fusion temperature using constructive-pruning hybrid method for RBF networks[J].Journal of Southeast University(English Edition), 2011, 27(2):159-163.[doi:10.3969/j.issn.1003-7985.2011.02.009]

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