Abstract
Considering the problem of invalid data caused mismatch of wavenumber spectrum which contained in turbulence observation data, an algorithm of turbulent wavenumber spectrum matching based on SVM is proposed. Category labels are obtained from pre-processed raw data by cross validation algorithm, and then the optimum parameters of the classifier are got through SVM learning algorithm. Sea trial data validation results indicate that the algorithm has high matching accuracy, and provides a new way to calculate the turbulence wavenumber spectrum matching.
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