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- W2392031702 abstract "Identification of underwater vehicle mechanical noise sources can be considered as a pattern recognition problem on small samples.Using the signals of multiple sensors is one of the most effective methods to solve the problem.Currently there is no appropriate method to calculate the weightiness of each sensor during the evaluation.In this paper,the transductive confidence machine(TCM) was used to calculate the confidence of classification prediction,which was an effective representation for the weightiness of each sensor.First,an improved strangeness measuring method was given to increase the accuracy of confidence prediction.Then a new algorithm,named TCM-IKNN-M(Transductive Confidence Machine for Improved K-Nearest Neighbors based on Multi_sensors),was proposed based on the predicted confidence and improved strangeness measuring method.The results of the experiment conducted on a cabin model show that TCM-IKNN-M algorithm can greatly increase the right rate of identification by fusing the information from multiple sensors." @default.
- W2392031702 created "2016-06-24" @default.
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- W2392031702 date "2010-01-01" @default.
- W2392031702 modified "2023-09-25" @default.
- W2392031702 title "Identification of noise sources based on multi-sensors information fusion" @default.
- W2392031702 hasPublicationYear "2010" @default.
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