Combining Kalman Filter and Artificial Neural Network for Time Series Prediction
| Autor: | Huei-Ming Lin, 林輝銘 |
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| Rok vydání: | 2005 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 93 Time is usually an important variable in the decisions of business. Since, when they analyzed, managers often predict the other corresponding variables by historical data, called time series. Time series prediction is a group of statistic data, which was predicted by some corresponding data happened during some time. The exactness of outcome of time series prediction would affect business planning and administration. Nowadays business and economical activities in essence are dynamic variable. In the face of environment characters and cost-benefit problems of real series prediction, how to choose suitable method of time series prediction is a very important issue for managers. How to develop a robust method for prediction of time series is the most important work of managers. In the thesis, we combined the Kalman filter, with artificial neural network, and fuzzy theory. We hope this could build a hybrid method to analyze time series by qualitative and quantitative method, to provide a reliable prediction method for the dynamic and variable time series of business and economical activities. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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