舰船电子工程
艦船電子工程
함선전자공정
SHIP ELECTRONIC ENGINEERING
2015年
1期
126-130
,共5页
灰色加权关联度%多尺度支持向量机%舰船备件%预测
灰色加權關聯度%多呎度支持嚮量機%艦船備件%預測
회색가권관련도%다척도지지향량궤%함선비건%예측
weighted grey correlation degree%multi-scale support vector machine%ship spare parts%forecast
运用灰色加权关联方法对影响远海舰船备件消耗的主要因素进行分析,以确定备件消耗影响因素的权重大小,以此为依据来筛选出主要影响因素,在此基础上运用支持向量机理论,建立灰色加权关联分析与多尺度最小二乘支持向量机组合的学习模型,将筛选得到的主要影响因素的样本值作为输入值进行学习训练,较好地解决了影响因素与备件消耗之间的非线性关系。实例应用表明,该模型对舰船备件需求的预测具有较高的精度。
運用灰色加權關聯方法對影響遠海艦船備件消耗的主要因素進行分析,以確定備件消耗影響因素的權重大小,以此為依據來篩選齣主要影響因素,在此基礎上運用支持嚮量機理論,建立灰色加權關聯分析與多呎度最小二乘支持嚮量機組閤的學習模型,將篩選得到的主要影響因素的樣本值作為輸入值進行學習訓練,較好地解決瞭影響因素與備件消耗之間的非線性關繫。實例應用錶明,該模型對艦船備件需求的預測具有較高的精度。
운용회색가권관련방법대영향원해함선비건소모적주요인소진행분석,이학정비건소모영향인소적권중대소,이차위의거래사선출주요영향인소,재차기출상운용지지향량궤이론,건립회색가권관련분석여다척도최소이승지지향량궤조합적학습모형,장사선득도적주요영향인소적양본치작위수입치진행학습훈련,교호지해결료영향인소여비건소모지간적비선성관계。실례응용표명,해모형대함선비건수구적예측구유교고적정도。
In order to get the weights of the factors which affect the spare parts consumption ,the weighted grey corre‐lation method was used to analyze the main factors which affect the pelagic ship spare parts consumption ,then the main influ‐encing factors were filtrated .On this basis ,the grey weighted correlation & multi‐scale least squares support vector machine training model was built by using SVM theory ,then the sample values of the main influencing factors were input the built training model for learning training ,the problem of the nonlinear relationship between the influencing factors and the spare parts consumption was solved preferably .The application example shows that the demand forecasting value of the ship spare parts consumption is higher accuracy by using the built model .