Application of decision tree algorithm in redundancy reduction of ship autonomous cruise data
Intelligent management and navigation of ships need to be completed according to reliable autonomous cruise data,and a large number of sensor data and monitoring information are used as input,so that the system can make correct decisions.However,these data may have redundant information interference,which affects the reliability of intelligent decision-making system.Therefore,the application of decision tree algorithm in ship autonomous cruise data redundancy is studied.Filtering,interpolation and hybrid time series data generation are used to process the time series of ship autonomous cruise data and generate standardized time series data of ship autonomous cruise.According to the processed data,a decision tree is generated to classify the autonomous cruise data of the ship;By calculating the data similarity between the same kind and designing the eliminator,the ship autonomous cruise data can be eliminated and the cruise data without redundancy can be obtained.The test results show that the algorithm has a good effect on data time series processing,which can divide different data categories and calculate the similarity between similar data,and the maximum space reduction ratio is 27.8％.
decision tree algorithmautonomous cruising of shipsdata redundancy eliminationtime series datadata similaritydata classification
NETL
NSTL
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