Investigation into the robustness of evolutionary programming regression for sedimentation study

Evolutionary Polynomial Regression (EPR) has been used to determine the total sediment load in selected rivers in Malaysia. In order to test the robustness and generalization ability of EPR modelling, the approach that is generally adopted is to test the performance of trained EPR mod...

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Main Author:	Nadiatul Adilah, Ahmad Abdul Ghani
Format:	Article
Language:	English
Published:	Asian Research Publishing Network (ARPN) 2016
Subjects:	TA Engineering (General). Civil engineering (General)
Online Access:	http://umpir.ump.edu.my/id/eprint/21731/ http://umpir.ump.edu.my/id/eprint/21731/ http://umpir.ump.edu.my/id/eprint/21731/1/Investigation%20into%20the%20robustness%20of%20evolutionary%20programming.pdf

id	ump-21731
recordtype	eprints
spelling	ump-217312018-07-24T01:25:39Z http://umpir.ump.edu.my/id/eprint/21731/ Investigation into the robustness of evolutionary programming regression for sedimentation study Nadiatul Adilah, Ahmad Abdul Ghani TA Engineering (General). Civil engineering (General) Evolutionary Polynomial Regression (EPR) has been used to determine the total sediment load in selected rivers in Malaysia. In order to test the robustness and generalization ability of EPR modelling, the approach that is generally adopted is to test the performance of trained EPR models on an independent validation set. If such performance is adequate, the model is deemed to be robust and able to generalize. When evaluating EPR models, consideration must be given not only to their predictive accuracy but also to the interpretive ability of the models. This can be done by carrying out a sensitivity analysis that quantifies the relative importance of model inputs to the corresponding outputs. In this paper, the robustness of EPR models is investigated in a case study of predicting the total sediment load at Malaysian rivers. A procedure that tests the robustness of the predictive ability of EPR models is introduced. The results indicate that the good performance of EPR models in the data used for model calibration and validation also perform in a robust fashion over a range of data used in the model calibration phase. The results also indicate that validating EPR models using the procedure applied in this study are essential in order to investigate their robustness. Asian Research Publishing Network (ARPN) 2016 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/21731/1/Investigation%20into%20the%20robustness%20of%20evolutionary%20programming.pdf Nadiatul Adilah, Ahmad Abdul Ghani (2016) Investigation into the robustness of evolutionary programming regression for sedimentation study. ARPN Journal of Engineering and Applied Sciences, 11 (3). pp. 1555-1561. ISSN 1819-6608 http://www.arpnjournals.org/jeas/research_papers/rp_2016/jeas_0216_3534.pdf
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	TA Engineering (General). Civil engineering (General)
spellingShingle	TA Engineering (General). Civil engineering (General) Nadiatul Adilah, Ahmad Abdul Ghani Investigation into the robustness of evolutionary programming regression for sedimentation study
description	Evolutionary Polynomial Regression (EPR) has been used to determine the total sediment load in selected rivers in Malaysia. In order to test the robustness and generalization ability of EPR modelling, the approach that is generally adopted is to test the performance of trained EPR models on an independent validation set. If such performance is adequate, the model is deemed to be robust and able to generalize. When evaluating EPR models, consideration must be given not only to their predictive accuracy but also to the interpretive ability of the models. This can be done by carrying out a sensitivity analysis that quantifies the relative importance of model inputs to the corresponding outputs. In this paper, the robustness of EPR models is investigated in a case study of predicting the total sediment load at Malaysian rivers. A procedure that tests the robustness of the predictive ability of EPR models is introduced. The results indicate that the good performance of EPR models in the data used for model calibration and validation also perform in a robust fashion over a range of data used in the model calibration phase. The results also indicate that validating EPR models using the procedure applied in this study are essential in order to investigate their robustness.
format	Article
author	Nadiatul Adilah, Ahmad Abdul Ghani
author_facet	Nadiatul Adilah, Ahmad Abdul Ghani
author_sort	Nadiatul Adilah, Ahmad Abdul Ghani
title	Investigation into the robustness of evolutionary programming regression for sedimentation study
title_short	Investigation into the robustness of evolutionary programming regression for sedimentation study
title_full	Investigation into the robustness of evolutionary programming regression for sedimentation study
title_fullStr	Investigation into the robustness of evolutionary programming regression for sedimentation study
title_full_unstemmed	Investigation into the robustness of evolutionary programming regression for sedimentation study
title_sort	investigation into the robustness of evolutionary programming regression for sedimentation study
publisher	Asian Research Publishing Network (ARPN)
publishDate	2016
url	http://umpir.ump.edu.my/id/eprint/21731/ http://umpir.ump.edu.my/id/eprint/21731/ http://umpir.ump.edu.my/id/eprint/21731/1/Investigation%20into%20the%20robustness%20of%20evolutionary%20programming.pdf
first_indexed	2023-09-18T22:32:00Z
last_indexed	2023-09-18T22:32:00Z
_version_	1777416347807907840

Investigation into the robustness of evolutionary programming regression for sedimentation study

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