{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T03:35:05Z","timestamp":1706758505872},"reference-count":27,"publisher":"World Scientific Pub Co Pte Lt","issue":"01","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J CIRCUIT SYST COMP"],"published-print":{"date-parts":[[2010,2]]},"abstract":"<jats:p> A prediction scheme for Ethernet traffic data using a Multiscale-Bilinear Recurrent Neural Network with Adaptive Learning (M-BRNN-AL) is proposed and presented in this paper. The proposed predictor integrates an M-BRNN and an AL algorithm. In M-BRNN, the wavelet transform is employed to decompose the original traffic signals into several simple traffic signals. A BRNN is then used to predict each decomposed traffic signal. An AL algorithm is also applied in order to improve the learning process at each resolution level in M-BRNN-AL. Experiments and results on a set of Ethernet network traffic predictions show that the proposed scheme converges faster and archives better prediction performance than the other conventional models such as the Multi-layer Perception Type Neural Network, BRNN, and the original M-BRNN in terms of the normalized mean square error. <\/jats:p>","DOI":"10.1142\/s0218126610005986","type":"journal-article","created":{"date-parts":[[2010,2,22]],"date-time":"2010-02-22T11:18:45Z","timestamp":1266837525000},"page":"155-171","source":"Crossref","is-referenced-by-count":4,"title":["LONG-TERM PREDICTION OF ETHERNET TRAFFIC USING MULTISCALE-BILINEAR RECURRENT NEURAL NETWORK WITH ADAPTIVE LEARNING"],"prefix":"10.1142","volume":"19","author":[{"given":"DONG-CHUL","family":"PARK","sequence":"first","affiliation":[{"name":"Intelligent Computing Research Laboratory, Department of Information Engineering, Myong Ji University, Yong In, KyungKi-do, 449-728, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2011,11,21]]},"reference":[{"key":"rf1","doi-asserted-by":"publisher","DOI":"10.1109\/TCOM.1987.1096886"},{"key":"rf3","first-page":"1139","volume":"9","author":"Fowler H. 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