Anzeige
Erschienen in:
2015 | OriginalPaper | Buchkapitel
27. Study on the Aerial Target’s Threat Degree Ordering Model Based on BP Neural Network
verfasst von : Songli Zhang, Yanfei Kong, Xiaohui Peng, Xiaogao Wang
Erschienen in: Proceedings of the 15th International Conference on Man–Machine–Environment System Engineering
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Abstract
This paper introduces the significance of air-raiding and anti-air-raiding for modern war and ordering of air attack targets to air defense, analyzes the influence index of aerial target’s threat degree, and determines the normalized treatment of these influence indexes. The paper brings in BP neural network theory and illustrates its algorithm steps and establishes the model of BP neural network, training using the constructed network to sort the threat degree of aerial targets. Result shows that the established BP neural network model has a strong nonlinear mapping ability and self-learning ability, it provides a reference for the air defense unit to evaluate aerial target’s threat degree, so could help commanders to make better decisions.