Using particle swarm optimization algorithm to optimize the order of the ARMA (p, q) model is feasible, and the use of the results of the ARMA model optimized air generator status trends analysis is very accurate, and the raw data showed aviation the generator status consistent trend. Calculated analysis of the results, the average relative error is small, only 1.38 , compared with the the ARMA model built before optimization, average relative error is reduced by 0.23 percentage points, to optimize the effect is obvious.

New ARMA model based on particle swarm optimization\AICARMA.m
...................................................\fitness7.m
...................................................\predict.m
...................................................\SecPSO7.asv
...................................................\SecPSO7.m
...................................................\xin.asv
...................................................\xin.m
New ARMA model based on particle swarm optimization

• We are an exchange download platform that only provides communication channels. The downloaded content comes from the internet. Except for download issues, please Google on your own.
• The downloaded content is provided for members to upload. If it unintentionally infringes on your copyright, please contact us.
• Please use Winrar for decompression tools
• If download fail, Try it againg or Feedback to us.
• If downloaded content did not match the introduction, Feedback to us，Confirm and will be refund.
• Before downloading, you can inquire through the uploaded person information

Nothing．