|Table of Contents|

Aviation ammunition consumption prediction model based onmutated particle swarm optimization and deep neural network(PDF)

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2018年06期
Page:
716-
Research Field:
Publishing date:

Info

Title:
Aviation ammunition consumption prediction model based onmutated particle swarm optimization and deep neural network
Author(s):
Tian DehongHe Jianmin
School of Economics and Management,Southeast University,Nanjing 211189,China
Keywords:
mutated particle swarm optimization deep neural network aviation ammunition combination forecasting model
PACS:
TJ410.1
DOI:
10.14177/j.cnki.32-1397n.2018.42.06.012
Abstract:
The forecasting of aviation ammunition training consumption is studied based on the mutated particle swarm optimization(MPSO)and the deep neural network(DNN)to improve the efficiency of supply. The optimal activation functions of each layer of the network are determined by the DNN,the optimal weights and thresholds of each layer of the network are obtained by the MPSO,and the aviation ammunition consumption prediction model MPSO-DNN is constructed. Experimental studies show the MPSO-DNN has a mean square error of 0.0009 in the prediction of five-year data. Compared with particle swarm optimization-deep neural network(PSO-DNN),DNN and back propagation neural network(BPNN),MPSO-DNN has better predictive performance.

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Last Update: 2018-12-30