Staff View: Comparative modelling of strength properties of hydrated-lime activated rice husk-ash (HARHA) modified soft soil for pavement construction purposes by artificial neural network (ANN) and fuzzy logic (FL)

Comparative modelling of strength properties of hydrated-lime activated rice husk-ash (HARHA) modified soft soil for pavement construction purposes by artificial neural network (ANN) and fuzzy logic (FL)

Artificial neural network and fuzzy logic based model soft-computing techniques were adapted in the research study for the evaluation of the expansive clay soil-HARHA mixture’s consistency limit, compressibility and mechanical strength properties. The problematic clay soil was stabilized with vary...

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Main Authors:	Onyelowe, K. C., Alaneme, G. U., Onyia, M. E., Bui Van, D., Dimonyeka, M. U., Nnadi, E., Ogbonna, C., Odum, L. O., Aju, D. E., Abel, C., Udousoro, I. M., Onukwugha, E.
Format:	Article
Language:	English
Published:	Penerbit Universiti Kebangsaan Malaysia 2021
Online Access:	http://journalarticle.ukm.my/17817/1/20.pdf http://journalarticle.ukm.my/17817/ https://www.ukm.my/jkukm/volume-332-2021/
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spelling	my-ukm.journal.178172022-01-02T08:02:53Z http://journalarticle.ukm.my/17817/ Comparative modelling of strength properties of hydrated-lime activated rice husk-ash (HARHA) modified soft soil for pavement construction purposes by artificial neural network (ANN) and fuzzy logic (FL) Onyelowe, K. C. Alaneme, G. U. Onyia, M. E. Bui Van, D. Dimonyeka, M. U. Nnadi, E. Ogbonna, C. Odum, L. O. Aju, D. E. Abel, C. Udousoro, I. M. Onukwugha, E. Artificial neural network and fuzzy logic based model soft-computing techniques were adapted in the research study for the evaluation of the expansive clay soil-HARHA mixture’s consistency limit, compressibility and mechanical strength properties. The problematic clay soil was stabilized with varying proportions of HARHA (stabilizing agent) which is an agricultural waste derivative from the milling of rice ranging from 0% to 12%; the utilization of the alkaline activated wastes encourages its recycling and re-use to obtain sustainable, eco-efficient and eco-friendly engineered infrastructure for use in the construction industry with economic benefits also. The obtained laboratory and experimental responses were taken as the system database for the ANN and fuzzy logic model development; the soil-HARHA proportions with their corresponding compaction and consistency limit characteristics were feed to the network as the model input variables while the mechanical strength (California-bearing-ratio (CBR), unconfined-compressive-strength (UCS) and Resistance value (R-values)) responses of the blended soil mixture were the model target variables. For the ANN model, feed forward back propagation and Levernberg Marquardt training algorithm were utilized for the model development with the optimized network architecture of 8-6-3 derived based on MSE performance criteria; while for the fuzzy logic model, the mamdani FIS with both triangular and trapezoidal membership function with both models formulated, simulated and computed using MATLAB toolbox. The models were compared in terms of accuracy of prediction using MAE, RMSE and coefficient of determination and from the computed results, 0.2750, 0.4154 and 0.9983 respectively for ANN model while 0.3737, 0.6654 and 0.9894 respectively was obtained for fuzzy logic model. The two models displayed robust characteristics and performed satisfactorily enabling the optimization of the solid waste derivatives utilization for soil mechanical properties improvement for engineering purposes. Penerbit Universiti Kebangsaan Malaysia 2021 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/17817/1/20.pdf Onyelowe, K. C. and Alaneme, G. U. and Onyia, M. E. and Bui Van, D. and Dimonyeka, M. U. and Nnadi, E. and Ogbonna, C. and Odum, L. O. and Aju, D. E. and Abel, C. and Udousoro, I. M. and Onukwugha, E. (2021) Comparative modelling of strength properties of hydrated-lime activated rice husk-ash (HARHA) modified soft soil for pavement construction purposes by artificial neural network (ANN) and fuzzy logic (FL). Jurnal Kejuruteraan, 33 (2). pp. 365-384. ISSN 0128-0198 https://www.ukm.my/jkukm/volume-332-2021/
institution	Universiti Kebangsaan Malaysia
building	Tun Sri Lanang Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Kebangsaan Malaysia
content_source	UKM Journal Article Repository
url_provider	http://journalarticle.ukm.my/
language	English
description	Artificial neural network and fuzzy logic based model soft-computing techniques were adapted in the research study for the evaluation of the expansive clay soil-HARHA mixture’s consistency limit, compressibility and mechanical strength properties. The problematic clay soil was stabilized with varying proportions of HARHA (stabilizing agent) which is an agricultural waste derivative from the milling of rice ranging from 0% to 12%; the utilization of the alkaline activated wastes encourages its recycling and re-use to obtain sustainable, eco-efficient and eco-friendly engineered infrastructure for use in the construction industry with economic benefits also. The obtained laboratory and experimental responses were taken as the system database for the ANN and fuzzy logic model development; the soil-HARHA proportions with their corresponding compaction and consistency limit characteristics were feed to the network as the model input variables while the mechanical strength (California-bearing-ratio (CBR), unconfined-compressive-strength (UCS) and Resistance value (R-values)) responses of the blended soil mixture were the model target variables. For the ANN model, feed forward back propagation and Levernberg Marquardt training algorithm were utilized for the model development with the optimized network architecture of 8-6-3 derived based on MSE performance criteria; while for the fuzzy logic model, the mamdani FIS with both triangular and trapezoidal membership function with both models formulated, simulated and computed using MATLAB toolbox. The models were compared in terms of accuracy of prediction using MAE, RMSE and coefficient of determination and from the computed results, 0.2750, 0.4154 and 0.9983 respectively for ANN model while 0.3737, 0.6654 and 0.9894 respectively was obtained for fuzzy logic model. The two models displayed robust characteristics and performed satisfactorily enabling the optimization of the solid waste derivatives utilization for soil mechanical properties improvement for engineering purposes.
format	Article
author	Onyelowe, K. C. Alaneme, G. U. Onyia, M. E. Bui Van, D. Dimonyeka, M. U. Nnadi, E. Ogbonna, C. Odum, L. O. Aju, D. E. Abel, C. Udousoro, I. M. Onukwugha, E.
spellingShingle	Onyelowe, K. C. Alaneme, G. U. Onyia, M. E. Bui Van, D. Dimonyeka, M. U. Nnadi, E. Ogbonna, C. Odum, L. O. Aju, D. E. Abel, C. Udousoro, I. M. Onukwugha, E. Comparative modelling of strength properties of hydrated-lime activated rice husk-ash (HARHA) modified soft soil for pavement construction purposes by artificial neural network (ANN) and fuzzy logic (FL)
author_facet	Onyelowe, K. C. Alaneme, G. U. Onyia, M. E. Bui Van, D. Dimonyeka, M. U. Nnadi, E. Ogbonna, C. Odum, L. O. Aju, D. E. Abel, C. Udousoro, I. M. Onukwugha, E.
author_sort	Onyelowe, K. C.
title	Comparative modelling of strength properties of hydrated-lime activated rice husk-ash (HARHA) modified soft soil for pavement construction purposes by artificial neural network (ANN) and fuzzy logic (FL)
title_short	Comparative modelling of strength properties of hydrated-lime activated rice husk-ash (HARHA) modified soft soil for pavement construction purposes by artificial neural network (ANN) and fuzzy logic (FL)
title_full	Comparative modelling of strength properties of hydrated-lime activated rice husk-ash (HARHA) modified soft soil for pavement construction purposes by artificial neural network (ANN) and fuzzy logic (FL)
title_fullStr	Comparative modelling of strength properties of hydrated-lime activated rice husk-ash (HARHA) modified soft soil for pavement construction purposes by artificial neural network (ANN) and fuzzy logic (FL)
title_full_unstemmed	Comparative modelling of strength properties of hydrated-lime activated rice husk-ash (HARHA) modified soft soil for pavement construction purposes by artificial neural network (ANN) and fuzzy logic (FL)
title_sort	comparative modelling of strength properties of hydrated-lime activated rice husk-ash (harha) modified soft soil for pavement construction purposes by artificial neural network (ann) and fuzzy logic (fl)
publisher	Penerbit Universiti Kebangsaan Malaysia
publishDate	2021
url	http://journalarticle.ukm.my/17817/1/20.pdf http://journalarticle.ukm.my/17817/ https://www.ukm.my/jkukm/volume-332-2021/
_version_	1724074612153647104
score	13.211869

Comparative modelling of strength properties of hydrated-lime activated rice husk-ash (HARHA) modified soft soil for pavement construction purposes by artificial neural network (ANN) and fuzzy logic (FL)

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