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Machine Learning Theory and Practice, 2022, 3(2); doi: 10.38007/ML.2022.030206.

Unmanned Ship Target Recognition System Based on Association Rules

Author(s)

Mayanker Lakshmi

Corresponding Author:
Mayanker Lakshmi
Affiliation(s)

University of Anbar, Iraq

Abstract

With the advent of the era of intelligence, the development of unmanned ship technology, greatly improve the efficiency of ocean monitoring, in civilian, unmanned ship can detect the sea surface weather conditions and underwater current, but also can monitor the sea surface ship accidents, illegal fishing and other phenomena; Militarily, unmanned vessels can conduct border patrols to monitor maritime violations and carry military weapons to safeguard China's maritime rights and interests. The purpose of this paper is to study the unmanned ship target recognition system based on association rule algorithm. From the point of view of system development, the hardware structure of unmanned ship target recognition system is put forward, and the system function module is described. The design of video acquisition, intelligent recognition, intelligent alarm, data transmission and other functional modules in the unmanned ship target recognition system is carried out with the idea of modularity. The association rule mining algorithm is used to mine the navigation beacon accident data, and the potential information mining is carried out in a variety of ways. The causes and internal rules of navigation beacon accidents are analyzed. The experimental results show that the southeast wind is easy to cause navigation beacon accidents due to natural causes under heavy rain.

Keywords

Association Rules, Unmanned Ship System, Target Recognition, Beacon Accident

Cite This Paper

Mayanker Lakshmi. Unmanned Ship Target Recognition System Based on Association Rules. Machine Learning Theory and Practice (2022), Vol. 3, Issue 2: 48-56. https://doi.org/10.38007/ML.2022.030206.

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