SE-DEA-SVM evaluation method of ECM operational disposition scheme

Operational disposition of electronic countermeasures (ECM) is a hot topic in modern warfare research. Through fully analyzing the characteristics and shortcomings of the traditional operational disposition scheme, a super-efficient data envelop-ment analysis support vector machine (SE-DEA-SVM) meth...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of systems engineering and electronics 2022-06, Vol.33 (3), p.600-611
Hauptverfasser: Zhao, Luda, Wang, Bin, He, Jun, Jiang, Xiaoping
Format: Artikel
Sprache:eng
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Operational disposition of electronic countermeasures (ECM) is a hot topic in modern warfare research. Through fully analyzing the characteristics and shortcomings of the traditional operational disposition scheme, a super-efficient data envelop-ment analysis support vector machine (SE-DEA-SVM) method for evaluating the operational configuration scheme of ECM is proposed. Firstly, considering the subjective and objective factors affecting the operational disposition of ECM, the index system of operational disposition scheme is established, and we explain the solution method of terminal indexs. Secondly, the evaluation and algorithm process of SE-DEA-SVM evaluation method are introduced. In this method, the super-efficient data envelopment analysis (SE-DEA) model is used to calculate the weight of index system, and the support vector machine (SVM) method combined with the training samples of evaluation index is used to obtain the input-output model of evaluation value of combat configura-tion. Finally, by an example (obtaining five schemes), we verify the SE-DEA-SVM evaluation method and analyze the results. The efficiency analysis, comparison analysis, and error analysis of this method are carried out. The results show that this method is more suitable for military evaluation with small samples, and it has high efficiency, applicability, and popularization value.
ISSN:1004-4132
1004-4132
DOI:10.23919/JSEE.2022.000058