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利用粒子群支持向量机预测轴流压气机机匣壁面压力
引用本文:熊纯,都昌兵,吴晓曦. 利用粒子群支持向量机预测轴流压气机机匣壁面压力[J]. 燃气涡轮试验与研究, 2011, 24(2): 20-22,48
作者姓名:熊纯  都昌兵  吴晓曦
作者单位:长沙航空职业技术学院,湖南,长沙,410124
摘    要:建立了基于粒子群优化的轴流压气机机匣压力支持向量机预测模型.利用支持向量机的强大非线性映射能力,实现了对某型轴流压气机机匣压力时间序列的非线性预测,并运用粒子群优化算法对支持向量机的重要参数进行了优化,增强了预测模型对混沌动力学的联想和泛化推理能力,提高了预测的精度和稳定性.而针对发动机台架试验数据的预测结果证明了方法...

关 键 词:压气机  粒子群优化  支持向量机  时间序列预测

Compressor Casing Pressure Prediction Based on Particle Swarm Optimization and Support Vector Machines
XIONG Chun,DU Chang-bing,WU Xiao-xi. Compressor Casing Pressure Prediction Based on Particle Swarm Optimization and Support Vector Machines[J]. Gas Turbine Experiment and Research, 2011, 24(2): 20-22,48
Authors:XIONG Chun  DU Chang-bing  WU Xiao-xi
Affiliation:XIONG Chun,DU Chang-bing,WU Xiao-xi(Changsha Aeronautical Vocational and Technical College,Changsha 410124,China)
Abstract:Based on particle swarm optimization and support vector machines,a forecasting model for compressor casing wall pressure is presented.The strong nonlinear mapping capability of the support vector machines is used to implement nonlinear forecasting of the measured time series of compressor casing wall pressure.Particle swarm optimization is employed to optimize important parameters of support vector machines.The association and generalization capabilities of forecasting model on chaos dynamics are increased,...
Keywords:compressor  particle swarm optimization  support vector machines  time series forecasting  
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