Mining of Association Rules in R Using Apriori Algorithm

Mehta, Anjali; Bura, Deepa

doi:10.1007/978-981-15-5341-7_14

Cited by 7 publications

(1 citation statement)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The association rule algorithm is developed by Agrawal and co-workers in order to automatically reveal the hidden association relationship among data items [11]- [17].…”

Section: Introduction To Association Rulesmentioning

confidence: 99%

Frame Synchronization Method Based on Association Rules for CNAV-2 Messages

Qian

2023

Chinese J. Elect.

View full text Add to dashboard Cite

The GPS system is a navigation satellite system with high precision, all-weather service, and global coverage, whose main purpose is to provide real-time and continuous global navigation services for the US military, and whose signal interference in wartime is a heavy blow to the US military. Its existing interference measures are classified into two types: blanket jamming and deception jamming, with the latter having better interference effects due to its imperceptibility. Frame synchronization, as the foundation of deception jamming, is a focus of current research on navigation countermeasures. This paper discusses the frame synchronization of CNAV-2 messages in GPS L1C signals and proposes a frame synchronization algorithm based on association rules. It analyzes the structural characteristics of CNAV-1 message data, reveals the hidden mapping relationships in the BCH code sequence of the first sub-frame by applying association rules, and achieves a blind synchronization of navigation messages by counting the types of mapping relationships and calculating the confidence levels. The simulation test results show that the proposed algorithm displays high error resilience and correct recognition rates and demonstrates certain values in engineering applications.

show abstract

“…The association rule algorithm is developed by Agrawal and co-workers in order to automatically reveal the hidden association relationship among data items [11]- [17].…”

Section: Introduction To Association Rulesmentioning

confidence: 99%