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船舶上层建筑整体纵向固有频率特性预报算法研究
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  • 英文篇名:Research on prediction algorithms for longitudinal natural frequency characteristics of overall ship superstructure
  • 作者:龚洁
  • 英文作者:GONG Jie;City College of Science and Technology Chongqing University;
  • 关键词:船舶上层建筑 ; 纵向固有频率 ; 证据理论 ; 变化特性 ; 组预报算法设计
  • 英文关键词:ship superstructure;;longitudinal natural frequency;;evidence theory;;change characteristics;;group prediction algorithm design
  • 中文刊名:JCKX
  • 英文刊名:Ship Science and Technology
  • 机构:重庆大学城市科技学院;
  • 出版日期:2019-06-23
  • 出版单位:舰船科学技术
  • 年:2019
  • 期:v.41
  • 语种:中文;
  • 页:JCKX201912002
  • 页数:3
  • CN:12
  • ISSN:11-1885/U
  • 分类号:5-7
摘要
为了提高船舶上层建筑整体纵向固有频率特性预报的精度,提出一种样本筛选与变权重的船舶上层建筑整体纵向固有频率特性组合预报算法。首先根据样本之间的相似性,选择与待预报点相关的船舶上层建筑整体纵向固有频率特性数据,然后根据采用多个算法从不同角度对船舶上层建筑整体纵向固有频率特性进行预报,最后采用证据理论对单一算法的权值进行估计,加权得到船舶上层建筑整体纵向固有频率特性预报结果,测试结果表明,本文算法的船舶上层建筑整体纵向固有频率特性预报精度高,克服了单一算法或者传组合算法的弊端,降低了船舶上层建筑整体纵向固有频率特性预报误差。
        In order to improve the accuracy of forecasting the longitudinal natural frequency characteristics of ship superstructure, a combined forecasting algorithm based on sample selection and variable weight is proposed. Firstly, according to the similarity between samples, the longitudinal natural frequency characteristic data of ship superstructure related to the predicted points are selected, then the longitudinal natural frequency characteristics of ship superstructure are predicted from different angles by using multiple algorithms. Finally, the weight of single algorithm is estimated by using evidence theory,and the longitudinal natural frequency of ship superstructure is obtained by weighting. The test results show that the proposed algorithm has high accuracy in predicting the longitudinal natural frequency characteristics of ship superstructure,overcomes the drawbacks of single algorithm or combined transmission algorithm, and reduces the prediction error of the longitudinal natural frequency characteristics of ship superstructure.
引文
[1]王墨,马骏.船舶上层建筑重量重心对其固有频率的影响[J].船舶标准化工程师,2015,48(2):25-29.
    [2]殷玉梅,赵德有,崔洪宇,等.基于支持向量机的船舶上层建筑纵向振动特性预报[J].中国造船,2011,52(3):115-121.
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    [4]李欣蔚,陈辉,张亚红.自回归滑动平均和相关向量机的信息系统安全态势估计[J].微电子学与计算机,2017,34(09):141-144.
    [5]姚宏洋,林晓烘,宗思光.基于时序的D-S证据理论雷达辐射源识别[J].舰船电子工程,2019,39(1):47-49+117.

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