帮我查个EI检索吧,题目是the application of improved elman neural network in the exchange rate time series已经查到了吗?我都不知道在哪里查呢,这个论文开始发表的时候是说EI和ISTP都可以检索的,能告诉我这两
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帮我查个EI检索吧,题目是the application of improved elman neural network in the exchange rate time series已经查到了吗?我都不知道在哪里查呢,这个论文开始发表的时候是说EI和ISTP都可以检索的,能告诉我这两
帮我查个EI检索吧,
题目是the application of improved elman neural network in the exchange rate time series
已经查到了吗?我都不知道在哪里查呢,
这个论文开始发表的时候是说EI和ISTP都可以检索的,能告诉我这两个怎么查的吗?
帮我查个EI检索吧,题目是the application of improved elman neural network in the exchange rate time series已经查到了吗?我都不知道在哪里查呢,这个论文开始发表的时候是说EI和ISTP都可以检索的,能告诉我这两
EI检索,这个是在http://www.engineeringvillage.com,但是是付费的.
Record 1 from Compendex for: ((the application of improved elman neural network in the exchange rate time series) WN TI), 1969-2011
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1. Accession number: 20110313596761
Title: The application of improved Elman neural network in the exchange rate time series
Authors: Tan, Hua1
Author affiliation: 1 College of Economic, Jiaxing University, Jiaxing, Zhejiang, China
Corresponding author: Tan, H.
Source title: Proceedings - International Conference on Artificial Intelligence and Computational Intelligence, AICI 2010
Abbreviated source title: Proc. - Int. Conf. Artif. Intell. Comput. Intell., AICI
Volume: 3
Monograph title: Proceedings - International Conference on Artificial Intelligence and Computational Intelligence, AICI 2010
Issue date: 2010
Publication year: 2010
Pages: 440-443
Article number: 5656516
Language: English
ISBN-13: 9780769542256
Document type: Conference article (CA)
Conference name: 2010 International Conference on Artificial Intelligence and Computational Intelligence, AICI 2010
Conference date: October 23, 2010 - October 24, 2010
Conference location: Sanya, China
Conference code: 83359
Sponsor: Hainan Province Institute of Computer; Qiongzhou University
Publisher: IEEE Computer Society, 445 Hoes Lane - P.O.Box 1331, Piscataway, NJ 08855-1331, United States
Abstract: In this paper, we select the Elman neural network method to improve because of its good non-linear effect of disturbance elimination, and present a new exchange rate time series prediction method. We point out a new improved Elman neural network model firstly, and then predict the time series of RMB exchange rate against U. S. dollar. Through the forecasting process, we determine the input variables for the network structure, and determine the neural network's critical parameters to forecasting. The results show that the improved Elman network can obtain better results during the forecasting process. © 2010 IEEE.
Number of references: 9
Main heading: Neural networks
Controlled terms: Forecasting - Time series - Time series analysis
Uncontrolled terms: Critical parameter - Disturbance elimination - Elman network - Elman neural network - Exchange rate forecasting - Exchange rates - Input variables - Network structures - Nonlinear effect - RMB exchange rate - Time series prediction
Classification code: 723.4 Artificial Intelligence - 922.2 Mathematical Statistics
DOI: 10.1109/AICI.2010.330
Database: Compendex
Compilation and indexing terms, © 2011 Elsevier Inc.