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- W2350868219 abstract "Based on the introduction of Glowworm Swarm Optimization(GSO) and Back-Propagation(BP) neural network,a target threat assessment model is proposed and its algorithm is developed.This model is based on GSO optimized BP network(GSOBP).In GSOBP,GSO is employed to simultaneously optimize the initial weights and thresholds of the BP neural network.Target threat database is adopted to test the performance of GSOBP in target threat prediction.The performance of GSOBP is compared with that of normal BP neural network and Particle Swarm Optimization and Support Vector Machines(PSO_SVM).Experiment results show that target threat prediction accuracy by GSOBP is higher than that by normal BP or by PSO_SVM." @default.
- W2350868219 created "2016-06-24" @default.
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- W2350868219 date "2013-01-01" @default.
- W2350868219 modified "2023-09-24" @default.
- W2350868219 title "Target threat assessment using glowworm swarm optimization and BP neural network" @default.
- W2350868219 hasPublicationYear "2013" @default.
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