Hybridization of nonlinear and linear models for time series forecasting
Nowadays, time series forecasting is very challenging due to the uncertainties of real world events that are influenced by many indefinite factors and rapid changes. This scenario requires forecasting methods that work efficiently with incomplete and multivariate data. Otherwise, the solutions will...
Saved in:
主要作者: | Salleh@Sallehuddin, Roselina |
---|---|
格式: | Thesis |
语言: | English |
出版: |
2010
|
主题: | |
在线阅读: | http://eprints.utm.my/id/eprint/18768/1/HamisanSalimMFP2010.pdf |
标签: |
添加标签
没有标签, 成为第一个标记此记录!
|
相似书籍
-
The comparative forecast performance of univariate and multivariate model: an application to time series forecasting
由: Sallehuddin, Roselina, et al.
出版: (2009) -
The enhanced group method of data handling models for time series forecasting
由: Samsudin, Ruhaidah
出版: (2012) -
Time series modeling and designing of artifical neural network (ANN) for revenue forecasting
由: Mohd. Yusof, Norfadzlia
出版: (2005) -
A hybrid approach based on arima and artificial neural networks for crime series forecasting
由: Mohd. Zaki, Mohd. Suhaimi
出版: (2014) -
Combining group method of data handling models using artificial bee colony algorithm for time series forecasting
由: Yahya, Nurhaziyatul Adawiyah
出版: (2019)