{"title":"基于CGA-SVM的损伤等级评估模型研究","authors":"Z. You, Q. Shi, Xianglong Ni, Ning Ding","doi":"10.1109/QR2MSE.2013.6625952","DOIUrl":null,"url":null,"abstract":"The battlefield damage level assessment is different from other assessment problems because of its characteristics such as small sample, multiple influence factors and high dimension. Thereby, the assessment methods like Bayesian Net (BN), Neutral Net (NN), and multiple indexes comprehensive method can't be used in this domain. So, a new method must be introduced. Then, Support Vector Mechanism (SVM) which can deal with the small sample, multi-indexes and high dimension events is seemed suitable to this problem. To reduce the complexity of the SVM model, Gauss formula is choose as the kernel function of SVM. The parameter of SVM is optimized by the Cloud Genetic Algorithm (CGA) which can accelerate the GA's searching rate and keep its search randomly to overcome falling into local optimal solution. The model has been proved to be efficient for damage level assessment via a case study.","PeriodicalId":140736,"journal":{"name":"2013 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE)","volume":"6 1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Notice of RetractionResearch on damage level assessment model based on CGA-SVM\",\"authors\":\"Z. You, Q. Shi, Xianglong Ni, Ning Ding\",\"doi\":\"10.1109/QR2MSE.2013.6625952\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The battlefield damage level assessment is different from other assessment problems because of its characteristics such as small sample, multiple influence factors and high dimension. Thereby, the assessment methods like Bayesian Net (BN), Neutral Net (NN), and multiple indexes comprehensive method can't be used in this domain. So, a new method must be introduced. Then, Support Vector Mechanism (SVM) which can deal with the small sample, multi-indexes and high dimension events is seemed suitable to this problem. To reduce the complexity of the SVM model, Gauss formula is choose as the kernel function of SVM. The parameter of SVM is optimized by the Cloud Genetic Algorithm (CGA) which can accelerate the GA's searching rate and keep its search randomly to overcome falling into local optimal solution. The model has been proved to be efficient for damage level assessment via a case study.\",\"PeriodicalId\":140736,\"journal\":{\"name\":\"2013 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE)\",\"volume\":\"6 1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-07-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/QR2MSE.2013.6625952\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/QR2MSE.2013.6625952","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Notice of RetractionResearch on damage level assessment model based on CGA-SVM
The battlefield damage level assessment is different from other assessment problems because of its characteristics such as small sample, multiple influence factors and high dimension. Thereby, the assessment methods like Bayesian Net (BN), Neutral Net (NN), and multiple indexes comprehensive method can't be used in this domain. So, a new method must be introduced. Then, Support Vector Mechanism (SVM) which can deal with the small sample, multi-indexes and high dimension events is seemed suitable to this problem. To reduce the complexity of the SVM model, Gauss formula is choose as the kernel function of SVM. The parameter of SVM is optimized by the Cloud Genetic Algorithm (CGA) which can accelerate the GA's searching rate and keep its search randomly to overcome falling into local optimal solution. The model has been proved to be efficient for damage level assessment via a case study.