ageneralapproachbasedonautocorrelationtodetermineinputvariablesofneuralnetworksfortimeseriesforecasting
文献类型：期刊论文
| 作者 | Huang Wei2; Nakamori Yoshiteru2; Wang Shouyang1
|
| 刊名 | journalofsystemsscienceandcomplexity
 |
| 出版日期 | 2004 |
| 卷号 | 017期号:003页码:297 |
| ISSN号 | 1009-6124 |
| 英文摘要 | Input selection is probably one of the most critical decision issues in neural network designing, because it has a great impact on forecasting performance. Among the many applications of artificial neural networks to finance, time series forecasting is perhaps one of the most challenging issues. Considering the features of neural networks, we propose a general approach called Autocorrelation Criterion (AC) to determine the inputs variables for a neural network. The purpose is to seek optimal lag periods, which are more predictive and less correlated. AC is a data-driven approach in that there is no prior assumptiona bout the models for time series under study. So it has extensive applications and avoids a lengthy experimentation and tinkering in input selection. We apply the approach to the determination of input variables for foreign exchange rate forecasting and conductcomparisons between AC and information-based in-sample model selection criterion. The experiment results show that AC outperforms information-based in-sample model selection criterion. |
| 语种 | 英语 |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/41205]  |
| 专题 | 系统科学研究所 |
| 作者单位 | 1.中国科学院数学与系统科学研究院 2.北陆先端科学技术大学院大学 |
| 推荐引用方式 GB/T 7714 | Huang Wei,Nakamori Yoshiteru,Wang Shouyang. ageneralapproachbasedonautocorrelationtodetermineinputvariablesofneuralnetworksfortimeseriesforecasting[J]. journalofsystemsscienceandcomplexity,2004,017(003):297. |
| APA | Huang Wei,Nakamori Yoshiteru,&Wang Shouyang.(2004).ageneralapproachbasedonautocorrelationtodetermineinputvariablesofneuralnetworksfortimeseriesforecasting.journalofsystemsscienceandcomplexity,017(003),297. |
| MLA | Huang Wei,et al."ageneralapproachbasedonautocorrelationtodetermineinputvariablesofneuralnetworksfortimeseriesforecasting".journalofsystemsscienceandcomplexity 017.003(2004):297. |
入库方式： OAI收割
来源：数学与系统科学研究院
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