The Appropriate Weight Fuzzy Time Series for the Stationary Data: Application for Forecasting of Ar (1) Process - Riswan Efendi - Grāmatas - LAP LAMBERT Academic Publishing - 9783659302596 - 2012. gada 14. novembris
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The Appropriate Weight Fuzzy Time Series for the Stationary Data: Application for Forecasting of Ar (1) Process

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This book presents the appropriate weight for forecasting of AR(1) process by using fuzzy time series concept. A determination of weight approach is based on left and right (LAR) relationship using a collection of variation of chronological number in a fuzzy logical group (FLG). In the forecasting rule, the weight can be attempted into two proposed methods, namely non-reversal and reversal methods. By using data are generated from the AR(1) model and simulation technique both methods have been compared respectively. The results show that average of mean square error (MSE) from non-reversal method is smaller than reversal method on forecasting of AR(1) process. Thus, both of methods can be considered for AR(1) process. In the end of this book, the proposed method can be trained and tested by using real data

Mediji Grāmatas     Paperback Book   (Grāmata ar mīksto vāku un līmēto muguru)
Izlaists 2012. gada 14. novembris
ISBN13 9783659302596
Izdevēji LAP LAMBERT Academic Publishing
Lapas 76
Izmēri 150 × 5 × 226 mm   ·   131 g
Valoda Vācu