Applications of RS_SVM in equipment maintenance costs prediction

doi:10.3778/j.issn.1002-8331.2010.31.062

Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (31): 222-224.DOI: 10.3778/j.issn.1002-8331.2010.31.062

• 工程与应用 • Previous Articles Next Articles

Applications of RS_SVM in equipment maintenance costs prediction

ZHOU Fu-jiang^1，2，TIAN Wei-feng¹，ZHU Xiao-dong¹

1.Department of Equipment Command & Management，Ordnance Engineering College，Shijiazhuang 050003，China
2.Zhenjiang Watercraft College of the PLA，Zhenjiang，Jiangsu 212003，China

Received:2009-03-23 Revised:2009-05-25 Online:2010-11-01 Published:2010-11-01
Contact: ZHOU Fu-jiang

RS_SVM在装备维修费用预测中的应用

周辅疆^1，2，田伟峰¹，朱小冬¹

1.军械工程学院装备指挥与管理系，石家庄 050003
2.镇江船艇学院，江苏镇江 212003

通讯作者: 周辅疆

Abstract

Abstract: Based on analyzing advantage and defect of the Rough Sets（RS） theory and Support Vector Machines（SVM），a minimum decision network combining RS and SVM in intelligence is brought forward.A kind of forecasting model based on RS-SVM is designed and applied on the prediction of equipment maintenance costs.An example of the prediction of equipment maintenance costs is given，and the result shows that the method can bring less error and better predicted precision compared with other methods.

Key words: Rough Sets（RS） theory, Support Vector Machines（SVM）, equipment maintenance costs, prediction

摘要： 在分析粗糙集和支持向量机原理及各自的优缺点基础上，提出将粗糙集与支持向量机相结合的方法，构建了基于粗糙集与支持向量机（RS-SVM）的预测模型，并将该模型应用于装备维修费用预测。以某装备维修费用为例进行实例验证，计算结果表明，这种方法比其他方法有更好的预测精度。

关键词: 粗糙集, 支持向量机, 装备维修费用, 预测

CLC Number:

TP181

ZHOU Fu-jiang^1，2，TIAN Wei-feng¹，ZHU Xiao-dong¹. Applications of RS_SVM in equipment maintenance costs prediction[J]. Computer Engineering and Applications, 2010, 46(31): 222-224.

周辅疆^1，2，田伟峰¹，朱小冬¹. RS_SVM在装备维修费用预测中的应用[J]. 计算机工程与应用, 2010, 46(31): 222-224.

[1]	HUANG Dongyi, YANG Bing, WU Zihao, KUANG Jiayi, YAN Zeming. Spatio-Temporal Fully Connected Convolutional Neural Networks for Citywide Cellular Prediction [J]. Computer Engineering and Applications, 2021, 57(9): 168-175.
[2]	YANG Li, WU Yi, WEI Debin, PAN Chengsheng. Satellite Network Traffic Prediction Based on Spatiotemporal Correlation [J]. Computer Engineering and Applications, 2021, 57(7): 101-106.
[3]	CHANG Hao, CHEN Xiaolei, ZHANG Aihua, LI Ce, LIN Dongmei. Continuous Blood Pressure Prediction Based on Improved SENet Convolutional Neural Network [J]. Computer Engineering and Applications, 2021, 57(7): 130-135.
[4]	LIU Ziyan, YUAN Lei, ZHU Mingcheng, MA Shanshan, CHEN Linzhouting. YOLOv3 Traffic sign Detection based on SPP and Improved FPN [J]. Computer Engineering and Applications, 2021, 57(7): 164-170.
[5]	ZHANG Rui, WU Boxiong, ZHANG Liyuan, ZHANG Bo. Human Trajectory Prediction Method for Complex Scenes [J]. Computer Engineering and Applications, 2021, 57(6): 138-143.
[6]	YANG Fengyu, HUANG Yaxuan, ZHOU Shijian, ZHENG Wei. Survey of Software Defect Prediction Combined with Multi-metrics [J]. Computer Engineering and Applications, 2021, 57(5): 10-24.
[7]	LI Shuo, LIANG Yi. Prediction Model of Execution Time for Batch Application in Spark [J]. Computer Engineering and Applications, 2021, 57(5): 79-87.
[8]	XU Xianfeng, CAI Lulu, ZHANG Li. Photovoltaic Power Generation Prediction Algorithm Based on MLP and DBN [J]. Computer Engineering and Applications, 2021, 57(3): 266-272.
[9]	ZHENG Jianfeng, WANG Yingming. Research on Efficiency Confidence Interval Prediction Model Based on DEA-BP Neural Network [J]. Computer Engineering and Applications, 2021, 57(3): 273-278.
[10]	AN Weichao, YAN Ting, ZHANG Nan, ZHANG Shan, XIANG Jie, CAO Rui, WANG Bin. Application of Pathological Image Texture Analysis in MSI Prediction of Gastric Cancer [J]. Computer Engineering and Applications, 2021, 57(24): 205-211.
[11]	CHEN Hai, QIAN Fulan, CHEN Jie, ZHAO Shu, ZHANG Yanping. Rating Prediction Model Based on Variational Auto-Encoder [J]. Computer Engineering and Applications, 2021, 57(22): 153-159.
[12]	YI Lingzhi, WANG Shitong, YI Fang, DENG Dong, YI Zhimin, JIANG Peng. Wind Farm Ultra-Short-Term Wind Speed Prediction Based on EEMDSE-ILSTM [J]. Computer Engineering and Applications, 2021, 57(22): 288-294.
[13]	WU Minghui, HOU Lingyan, WANG Chao. Improved Mechanism of Prediction-Oriented Long Short-Term Memory Neural Network [J]. Computer Engineering and Applications, 2021, 57(21): 109-115.
[14]	ZHAO Yu, ZHU Yi, YU Qiao, CHEN Xiaoying. Cross Project Defect Prediction Method Based on Hierarchical Data Screening [J]. Computer Engineering and Applications, 2021, 57(20): 279-286.
[15]	ZHANG Xueting, CHENG Hua, FANG Yiquan. Prediction of Co-authorship Based on Meta-Path and Node Attributes [J]. Computer Engineering and Applications, 2021, 57(2): 164-169.

Applications of RS_SVM in equipment maintenance costs prediction

RS_SVM在装备维修费用预测中的应用

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics