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nutrilite金虫 (著名写手)
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怎么看一篇论文是被SCI还是ISTP收录？ 已有3人参与
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在web of science 里怎么看一篇论文是被SCI还是ISTP收录？下面这篇算么 A Novel Evolving Clustering Algorithm with Polynomial Regression for Chaotic Time-Series Prediction Author(s): Widiputra H (Widiputra, Harya)1, Kho H (Kho, Henry), Lukas (Lukas), Pears R (Pears, Russel)1, Kasabov N (Kasabov, Nikola) Editor(s): Leung CS; Lee M; Chan JH Source: NEURAL INFORMATION PROCESSING, PT 2, PROCEEDINGS Book Series: Lecture Notes in Computer Science Volume: 5864 Pages: 114-121 Published: 2009 Times Cited: 0 References: 9 Conference Information: 16th International Conference on Neural Information Processing (ICONIP 2009) King Mongluts Univ Technol Thonburi, Sch Informat Technol, Bangkok, THAILAND, DEC 01-05, 2009 Asia Pacific Neural Network Assembly; Int Neural Network Soc; Japanese Neural Network Soc; European Neural Network Soc; IEEE Computat Intelligence Soc Abstract: Time-series prediction has been a very well researched topic in recent studies. Some popular approaches to this problem are the traditional statistical methods e.g. multiple linear regression and moving average, and neural network with the Multi Layer Perceptron which has shown its supremacy in time-series prediction. In this study, we used a different approach based on evolving clustering algorithm with polynomial regressions to find repeating local patterns in a time-series data. To illustrate chaotic time-series data we have taken into account the use of stock price data from Indonesian stock exchange market and currency exchange rate data. In addition, we have also conducted a benchmark test using the Mackey Glass data set. Results showed that the algorithm offers a considerably high accuracy in time-series prediction and could also reveal repeating patterns of movement from the past. Document Type: Proceedings Paper Language: English Author Keywords: evolving clustering algorithm; polynomial regression; chaotic time-series data KeyWords Plus: DISCOVERY Reprint Address: Widiputra, H (reprint author), Auckland Univ Technol, Knowledge Engn & Discovery Res Inst, Auckland, New Zealand Addresses: 1. Auckland Univ Technol, Knowledge Engn & Discovery Res Inst, Auckland, New Zealand E-mail Addresses: harya.widiputra@aut.ac.nz, henry@student.sgu.ac.id, lukas@atmajaya.ac.id, russel.pears@aut.ac.nz, nikola.kasabov@aut.ac.nz Publisher: SPRINGER-VERLAG BERLIN, HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY IDS Number: BPM40 ISSN: 0302-9743 ISBN: 978-3-642-10682-8 [ Last edited by nutrilite on 2010-9-8 at 13:25 ] |
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nutrilite
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