A method of extreme learning machine spectrum model to judge the origin of fresh leaves of Enshi Yulu tea
A technology of extreme learning machines and fresh tea leaves, applied in scientific instruments, material analysis through optical means, instruments, etc., can solve the problems of reducing model prediction effect, unfavorable model robustness, long modeling time, etc., to improve modeling Rate and forecast effects, objective forecasts, effects of simplified model structure
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[0035] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.
[0036] A method of extreme learning machine spectrum model to distinguish the origin of fresh leaves of Enshi Yulu tea. It scans and obtains the near-infrared spectra of fresh tea leaves samples from different origins, and then preprocesses the spectra of the samples to remove noise information, and then converts the spectra of the samples into pairs The data points are saved in the excel table; then the spectral data are divided into 20 spectral sub-intervals, and the ant colony algorithm is used to accurately screen the spectral information sub-interval bands reflecting the origin of fresh leaves; finally, the best spectral information sub-interval information is input In the extreme learning machine algorithm, by continuously and repeatedly optimizing the number of neurons and activation functions of the extreme learning machine, th...
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