{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,1]],"date-time":"2022-04-01T23:05:12Z","timestamp":1648854312321},"reference-count":13,"publisher":"World Scientific Pub Co Pte Lt","issue":"04","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Model. Simul. Sci. Comput."],"published-print":{"date-parts":[[2017,12]]},"abstract":" With the aim of solving the detection problems for current complex event detection models in detecting a related event for a complex event from the high proportion disordered RFID event stream due to its big uncertainty arrival, an efficient complex event detection model based on Extended Nondeterministic Finite Automaton (ENFA) is proposed in this paper. The achievement of the paper rests on the fact that an efficient complex event detection model based on ENFA is presented to successfully realize the detection of a related event for a complex event from the high proportion disordered RFID event stream. Specially, in our model, we successfully use a new ENFA-based complex event detection model instead of an NFA-based complex event detection model to realize the detection of the related events for a complex event from the high proportion disordered RFID event stream by expanding the traditional NFA-based detection model, which can effectively address the problems above. The experimental results show that the proposed model in this paper outperforms some general models in saving detection time, memory consumption, detection latency and improving detection throughput for detecting a related event of a complex event from the high proportion out-of-order RFID event stream. <\/jats:p>","DOI":"10.1142\/s1793962317500490","type":"journal-article","created":{"date-parts":[[2017,4,25]],"date-time":"2017-04-25T06:16:25Z","timestamp":1493100985000},"page":"1750049","source":"Crossref","is-referenced-by-count":1,"title":["An efficient complex event detection model for high proportion disordered RFID event stream"],"prefix":"10.1142","volume":"08","author":[{"given":"Jianhua","family":"Wang","sequence":"first","affiliation":[{"name":"College of Electronic Engineering, South China Agricultural University, Guangzhou, P. R. 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