MODEL HYBRID JARINGAN SYARAF BACKPROPAGATION DAN REGRESI FUZZY UNTUK PERAMALAN DATA TIME SERIES
In this thesis hybrid models Backpropagation of neural network and fuzzy regression model are formed to improve the effectiveness of the performance of fuzzy regression models using Backpropagation of neural network performance for forecasting the case of incomplete data or the use of data in very s...
محفوظ في:
| المؤلفون الرئيسيون: | , |
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| التنسيق: | Theses and Dissertations NonPeerReviewed |
| منشور في: |
[Yogyakarta] : Universitas Gadjah Mada
2013
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://repository.ugm.ac.id/118811/ http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=58787 |
| الوسوم: |
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| المؤسسة: | Universitas Gadjah Mada |
| الملخص: | In this thesis hybrid models Backpropagation of neural network and
fuzzy regression model are formed to improve the effectiveness of the performance
of fuzzy regression models using Backpropagation of neural network performance
for forecasting the case of incomplete data or the use of data in very small
amounts and short period. In the implementation procedure, the output of the
optimization process Backpropagation of neural network used as input to the
fuzzy regression to obtain the minimum fuzzy interval.
In this study, empirical data analysis of monthly Consumer Price Index
(CPI) data and exchange rates Rupiah used in the application of hybrid models
are presented. Proposed hybrid model is able to provide the smallest possible
interval that includes all the actual data in it. Thus presenting the hybrid model is
intended to provide a reference for decision-makers to look at the best and worst
possible conditions of the observations made |
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