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- W2382143357 abstract "Based on the test data analysis method,characteristic parameters of mangroves,i.e.average basal diameter,the number of basal diameter,average diameter at breast-high(DBH),the number of DBH were extracted,and the artificial neural network model was developed to predict the height of mangroves.The back propagation(BP)algorithm was improved by using the Levenberg-Marquardt optimizing arithmetic.The heights of mangroves in the sampling points which are 25,50 and 75 m away from the dam were predicted using the trained BP neural network,standard errors are 0.000 6,0.002 2 and 0.004 1,with the correlation coefficients of 0.99,0.95 and 0.94.Results show that using BP neural network to predict the height of mangroves is feasible." @default.
- W2382143357 created "2016-06-24" @default.
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- W2382143357 date "2012-01-01" @default.
- W2382143357 modified "2023-09-23" @default.
- W2382143357 title "Prediction of height of Quanzhouwan mangroves based on BP neural networks" @default.
- W2382143357 hasPublicationYear "2012" @default.
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