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Prediction of Ship Roll Based on Second Diagonal Recurrent Neural Network 被引量:1

Prediction of Ship Roll Based on Second Diagonal Recurrent Neural Network
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出处 《控制工程期刊(中英文版)》 2013年第3期106-110,共5页 Scientific Journal of Control Engineering
关键词 控制工程 自动控制 自动化 USTC Second Diagonal Recurrent Neural Network (SDRNN) Stochastic Gradient Descent Algorithm Time SeriesPrediction Ship Rolling Motion
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同被引文献14

  • 1JIAChun-yu LIUHong-min ZHOUHui-feng.Fuzzy Control System of Hydraulic Roll Bending Based on Genetic Neural Network[J].Journal of Iron and Steel Research(International),2005,12(3):22-27. 被引量:2
  • 2刘建昌,王柱.基于神经网络模式识别的板形模糊控制器[J].东北大学学报(自然科学版),2005,26(8):718-721. 被引量:8
  • 3贾春玉,单修迎,牛召平.自调整动态神经网络模型及其在带材板形预测中的应用[J].钢铁研究学报,2006,18(12):50-53. 被引量:4
  • 4刘建昌,陈莹莹,张瑞友.基于PSO-BP网络的板形智能控制器[J].控制理论与应用,2007,24(4):674-678. 被引量:17
  • 5LAURINEN P, RONIBG J. An adaptive neural network model for predicting the post roughing mill temperature of steel slabs in the reheating furnace [ J ]. Journal of Materials Processing Technology, 2005, 168 ( 3 ) :423-430.
  • 6SHIM M, LEE K Y, LEE D S. Intelligent controller design for the flatness control in cold rolling process [ C ]// Proceedings of the 40th IEEE Conf on Decision and Control. Orlando: IEEE, 2001: 2720-2725.
  • 7BARRIOS J A, TORRES-ALVARADO M, CAVAZOS A. Neural fuzzy and Grey-Box modelling of entry temperature prediction in a hot strip mill [ J ]. Expert Systems with Application, 2012, 39 (3) : 3374-3384.
  • 8SON J S, LEE D M, KIM I S, et al. A study on on-line learning neural network for prediction for rolling force in hot-rolling mill [ J ]. Journal of Materials Processing Technology, 2005, 164-165 : 1612-1617.
  • 9SIKDAR S, KUMARI S. Neural network model of the profile of hot-rolled strip [ J ]. The International Journal of Advanced Manufacturing Technology, 2009, 42 ( 5 ) : 450-462.
  • 10GUDISE V G, ven AYAGAMOORTHY K. Comparison of particle swarm optimization and back propagation as training algorithms for neural networks [ C ]//Proceedings of the 2003 IEEE on Swarm Intelligence Symposium (SIS' 03). Indianapolis : IEEE, 2003 : 110-117.

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