摘要
船舶数据设备种类在不断增加,目前船舶数据调度方法在实际应用存在调度量低且精准度差的情况。因此对基于大数据的船舶网络数据资源调度模型进行构建,通过对模型特点分析后,进行大数据船舶网络数据资源调度模型构建,模型通过对大数据相似度进行计算后对数据中干扰进行过滤,对过滤后数据进行子任务量分配,从而对整体数据定义分类,最终实现分类后的大数据调度。通过仿真实验,对船舶网络大数据资源调度模型与传统船舶网络数据调度方法的数据调度总量以及数据调度精准度进行对比,证明模型构建的有效性。
The types of ship data equipment are also increasing.At present,there are low adjustment measures and poor accuracy in the practical application of ship data scheduling method.Therefore,the ship network data resource scheduling model based on big data is constructed.after analyzing the characteristics of the model,the big data ship network data resource scheduling model is constructed.after calculating big data similarity,the model filters the interference in the data,allocates the filtered data progress subtask quantity,thus realizes the whole data definition classification,and finally realizes the big data scheduling after classification.Through the simulation experiment,the big data resource scheduling model of ship network and the traditional ship are analyzed.In the network data scheduling method,the total amount of data scheduling and the accuracy of data scheduling are compared to prove the effectiveness of the model construction.
作者
杜力
DU Li(Changjiang Polytechnic,Wuhan 430074,China)
出处
《舰船科学技术》
北大核心
2019年第18期157-159,共3页
Ship Science and Technology
关键词
大数据
船舶
网络
资源调度
big data
shipping
network
scheduling of resources