基于聚类算法的散货码头装卸车作业任务的智能识别系统  

Intelligent Identification System for Loading and Unloading Vehicle Operations in Bulk Terminals Based on Clustering Algorithm

作　　者：刘温良 彭国兰[2] LIU Wenliang;PENG Guolan(School of Information Engineering,Xiamen Ocean Vocational College,Xiamen,Fujian 361100,China;School of Artificial Intelligence,Xiamen City University,Xiamen,Fujian 361008,China)

机构地区：[1]厦门海洋职业技术学院信息工程学院,福建厦门361100 [2]厦门城市职业学院人工智能学院,福建厦门361008

出　　处：《福建技术师范学院学报》2024年第5期64-74,共11页JOURNAL OF FUJIAN POLYTECHNIC NORMAL UNIVERSITY

摘　　要：文章提出一种针对散货码头装卸车作业任务的智能识别系统.该系统采用车载北斗定位模块和RFID技术,精确采集装卸车在作业泊位的定位信息;然后,采用K-means聚类算法对定位数据进行分析,实现对装卸车作业任务的智能识别.此外,配套开发了应用软件,便于实际操作和管理.实践证明,该系统能准确识别作业任务,自动记录作业趟次,激发装卸司机的工作积极性,提高码头运营效率.This study proposes an intelligent identification system for loading and unloading vehicle operations in bulk terminals.Firstly,based on adoption of the on-board Beidou positioning module and RFID technology,the system accurately collects positioning information of loading and unloading vehicles in the operational berths.Secondly,the K-means clustering algorithm is employed to analyze the positioning data with the aim of realizing the intelligent identification of loading and unloading tasks.Lastly,application software has been developed to facilitate practical operations and management.Generally speaking,practice has proved that the intelligent identification system can effectively identify the operation tasks of the loading and unloading vehicles,automatically record the number of operations,stimulate the enthusiasm of loading and unloading drivers,and improve the efficiency of terminal operations.

关 键 词：散货码头 装卸 智能识别 北斗定位 K-MEANS算法 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]