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船舶定位信号短时中断下的插值预测模型 预览 被引量:1

Interpolation Predictive Model under Short-Term Interrupting of Ship Positioning Signal
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摘要 根据基于时间序列的船舶航行定位数据的特征,在差分自回归移动平均模型的基础上,运用马尔可夫链状态转移概率特性解决非平稳数据的预测问题,在建立马尔可夫链状态迁移概率矩阵过程中,使用K-means聚类算法划分预测值与真实值的差值状态区间,继而构建出优化预测算法。对算法进行了理论分析和数值实验,并与其他算法进行了比较,结果表明,该优化算法在船舶定位数据短时预测领域具有较好的预测效果,优于多个其他算法,可应用于船舶移动定位产品中。 In accordance with the characteristics of ship navigation positioning data based on time series, the transition probability feature of the Markov chain state is utilized to solve the predictive problem of relatively great random volatility based on autoregressive integrated moving average model. During the process of building the probability matrix of Markov chain state transition, the K-means clustering algorithm is used to divide the differential state interval between predicted value and true value, and then a set of optimized predictive algorithm model is built. The value experiment on the algorithm and its comparison with other algorithms show that this optimized algorithm has better predictive effect when it comes to short-term predication of the ship navigation positioning data. It is better than other algorithms and can be applied to mobile positioning products for ships.
作者 阮群生 李豫颖 龚子强 RUAN Qunsheng, LI Yuying, GONG Ziqiang( 1. Department of Computer, Ningde Normal University, Ningde, Fujian 352100, China ;2. Office of Shipping Management, Ningde Maritime Affairs Bureau, Ningde, Fujian 352100, China)
出处 《计算机科学与探索》 CSCD 2014年第12期1525-1536,共12页 Egamer
基金 The Natural Science Foundation of Fujian Province of China under Grant No.2011J01357(福建省自然科学基金) the Fujian Education Department Foundation of China under Grant No. JA13337(福建省教育厅A类项目) the Service Western Foundation of Ningde Normal University under Grant Nos.2011H205,2013F32(宁德师范学院服务海西项目) the Creative Team Foundation of Ningde Normal University under Grant No.2013T08(宁德师范学院创新团队项目).
关键词 差分自回归移动平均模型(ARIMA) 马尔可夫链 K-MEANS 定位数据预测 autoregressive integrated moving average model (ARIMA) Markov chain K-means positioning data prediction
作者简介 阮群生(1979-),男,江西上饶人,2008年于东华理工大学获得硕士学位,现为宁德师范学院讲师,主要研究领域为算法分析与设计,软件理论与技术等。发表学术论文8篇,其中EI检索期刊论文2篇,核心论文4篇,主持各类项目7项。 李豫颖(1962-),女,贵州安顺人,宁德师范学院计算机系教授,主要研究领域信息系统理论与应用,数据辨识与应用,P-集合等。 龚子强(1984-),男,江西上饶人,2012年于世界海事大学获得硕士学位,现为宁德市海事局航运管理处副处长,主要研究领域为通航管理,航海信息处理等。
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