Authenticating ANN-NAR and ANN-NARMA models utilizing bootstrap techniques
Neural system procedures have a colossal reputation in the space of gauging. In any case, there is yet to be a sure strategy that can well accept the last model of the neural system time arrangement demonstrating. Thus, this paper propose a way to deal with accepting the said displaying utilizing ti...
| Main Authors: | , , , |
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| Format: | Proceeding Paper |
| Language: | English English English |
| Published: |
Springer, Cham
2017
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/56975/ http://irep.iium.edu.my/56975/19/56975_Authenticating%20ANN-NAR%20and%20ANN-NARMA_complete.pdf http://irep.iium.edu.my/56975/2/56975_Authenticating%20ANN-NAR_SCOPUS.pdf http://irep.iium.edu.my/56975/13/56975%20Authenticating%20ANN-NAR%20and%20ANN-NARMA%20WOS.pdf |
| _version_ | 1848784844187762688 |
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| author | Md. Ghani, Nor Azura Ahmad Kamaruddin, Saadi Mohamed Ramli, Norazan Selamat, Ali |
| author_facet | Md. Ghani, Nor Azura Ahmad Kamaruddin, Saadi Mohamed Ramli, Norazan Selamat, Ali |
| author_sort | Md. Ghani, Nor Azura |
| building | IIUM Repository |
| collection | Online Access |
| description | Neural system procedures have a colossal reputation in the space of gauging. In any case, there is yet to be a sure strategy that can well accept the last model of the neural system time arrangement demonstrating. Thus, this paper propose a way to deal with accepting the said displaying utilizing time arrangement square bootstrap. This straightforward technique is different compared to the traditional piece bootstrap of time-arrangement based, where it was composed by making utilization of every information set in the information apportioning procedure of neural system demonstrating; preparing set, testing set and approval set. At this point, every information set was separated into two little squares, called the odd and even pieces (non-covering pieces). At that point, from every piece, an arbitrary inspecting with substitution in a rising structure was made, and these duplicated tests can be named as odd-even square bootstrap tests. In time, the examples were executed in the neural system preparing for last voted expectation yield. The proposed strategy was forced on both manufactured neural system time arrangement models, which were nonlinear autoregressive (NAR) and nonlinear autoregressive moving normal (NARMA). In this study, three changing genuine modern month to month information of Malaysian development materials value records from January 1980 to December 2012 were utilized. It was found that the suggested bootstrapped neural system time arrangement models beat the first neural system time arrangement models. |
| first_indexed | 2025-11-14T16:43:42Z |
| format | Proceeding Paper |
| id | iium-56975 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English English English |
| last_indexed | 2025-11-14T16:43:42Z |
| publishDate | 2017 |
| publisher | Springer, Cham |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-569752019-08-27T01:52:29Z http://irep.iium.edu.my/56975/ Authenticating ANN-NAR and ANN-NARMA models utilizing bootstrap techniques Md. Ghani, Nor Azura Ahmad Kamaruddin, Saadi Mohamed Ramli, Norazan Selamat, Ali RB Pathology RD Surgery RG Gynecology and obstetrics Neural system procedures have a colossal reputation in the space of gauging. In any case, there is yet to be a sure strategy that can well accept the last model of the neural system time arrangement demonstrating. Thus, this paper propose a way to deal with accepting the said displaying utilizing time arrangement square bootstrap. This straightforward technique is different compared to the traditional piece bootstrap of time-arrangement based, where it was composed by making utilization of every information set in the information apportioning procedure of neural system demonstrating; preparing set, testing set and approval set. At this point, every information set was separated into two little squares, called the odd and even pieces (non-covering pieces). At that point, from every piece, an arbitrary inspecting with substitution in a rising structure was made, and these duplicated tests can be named as odd-even square bootstrap tests. In time, the examples were executed in the neural system preparing for last voted expectation yield. The proposed strategy was forced on both manufactured neural system time arrangement models, which were nonlinear autoregressive (NAR) and nonlinear autoregressive moving normal (NARMA). In this study, three changing genuine modern month to month information of Malaysian development materials value records from January 1980 to December 2012 were utilized. It was found that the suggested bootstrapped neural system time arrangement models beat the first neural system time arrangement models. Springer, Cham 2017-02-26 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/56975/19/56975_Authenticating%20ANN-NAR%20and%20ANN-NARMA_complete.pdf application/pdf en http://irep.iium.edu.my/56975/2/56975_Authenticating%20ANN-NAR_SCOPUS.pdf application/pdf en http://irep.iium.edu.my/56975/13/56975%20Authenticating%20ANN-NAR%20and%20ANN-NARMA%20WOS.pdf Md. Ghani, Nor Azura and Ahmad Kamaruddin, Saadi and Mohamed Ramli, Norazan and Selamat, Ali (2017) Authenticating ANN-NAR and ANN-NARMA models utilizing bootstrap techniques. In: 9th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2017), 3rd-5th April 2017, Kanazawa, Japan. https://link.springer.com/chapter/10.1007/978-3-319-54472-4_71 10.1007/978-3-319-54472-4_71 |
| spellingShingle | RB Pathology RD Surgery RG Gynecology and obstetrics Md. Ghani, Nor Azura Ahmad Kamaruddin, Saadi Mohamed Ramli, Norazan Selamat, Ali Authenticating ANN-NAR and ANN-NARMA models utilizing bootstrap techniques |
| title | Authenticating ANN-NAR and ANN-NARMA models utilizing bootstrap techniques |
| title_full | Authenticating ANN-NAR and ANN-NARMA models utilizing bootstrap techniques |
| title_fullStr | Authenticating ANN-NAR and ANN-NARMA models utilizing bootstrap techniques |
| title_full_unstemmed | Authenticating ANN-NAR and ANN-NARMA models utilizing bootstrap techniques |
| title_short | Authenticating ANN-NAR and ANN-NARMA models utilizing bootstrap techniques |
| title_sort | authenticating ann-nar and ann-narma models utilizing bootstrap techniques |
| topic | RB Pathology RD Surgery RG Gynecology and obstetrics |
| url | http://irep.iium.edu.my/56975/ http://irep.iium.edu.my/56975/ http://irep.iium.edu.my/56975/ http://irep.iium.edu.my/56975/19/56975_Authenticating%20ANN-NAR%20and%20ANN-NARMA_complete.pdf http://irep.iium.edu.my/56975/2/56975_Authenticating%20ANN-NAR_SCOPUS.pdf http://irep.iium.edu.my/56975/13/56975%20Authenticating%20ANN-NAR%20and%20ANN-NARMA%20WOS.pdf |