Our study aims to introduce a new quantitative workflow that integrates neural networks (NNs) and multi criteria decision analysis (MCDA). Existing MCDA workflows reveal a number of drawbacks, because of the reliance on human knowledge in the weighting stage. Thus, new workflow presented to form suitability maps at the regional scale for solid waste planning based on NNs. A feed-forward neural network employed in the workflow. A total of 34 criteria were pre-processed to establish the input dataset for NN modelling. The final learned network used to acquire the weights of the criteria. Accuracies of 95.2% and 93.2% achieved for the training dataset and testing dataset, respectively. The workflow was found to be capable of reducing human interference to generate highly reliable maps. The proposed workflow reveals the applicability of NN in generating landfill suitability maps and the feasibility of integrating them with existing MCDA workflows.
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16 October 2017
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE OF GLOBAL NETWORK FOR INNOVATIVE TECHNOLOGY AND AWAM INTERNATIONAL CONFERENCE IN CIVIL ENGINEERING (IGNITE-AICCE’17): Sustainable Technology And Practice For Infrastructure and Community Resilience
8–9 August 2017
Penang, Malaysia
Research Article|
October 16 2017
Quantitative workflow based on NN for weighting criteria in landfill suitability mapping Available to Purchase
Sohaib K. M. Abujayyab;
Sohaib K. M. Abujayyab
a)
1
School of Civil Engineering, Engineering Campus, Universiti Sains Malaysia
, 14300 Nibong Tebal, P. Pinang, Malaysia
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Mohd Sanusi S. Ahamad;
Mohd Sanusi S. Ahamad
b)
1
School of Civil Engineering, Engineering Campus, Universiti Sains Malaysia
, 14300 Nibong Tebal, P. Pinang, Malaysia
2
Solid Waste Management Cluster, Science and Engineering Research Centre, Engineering Campus, Universiti Sains Malaysia
, 14300 Nibong Tebal, Penang, Malaysia
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Ahmad Shukri Yahya;
Ahmad Shukri Yahya
c)
1
School of Civil Engineering, Engineering Campus, Universiti Sains Malaysia
, 14300 Nibong Tebal, P. Pinang, Malaysia
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Siti Zubaidah Ahmad;
Siti Zubaidah Ahmad
d)
1
School of Civil Engineering, Engineering Campus, Universiti Sains Malaysia
, 14300 Nibong Tebal, P. Pinang, Malaysia
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Mutasem Sh. Alkhasawneh;
Mutasem Sh. Alkhasawneh
e)
1
School of Civil Engineering, Engineering Campus, Universiti Sains Malaysia
, 14300 Nibong Tebal, P. Pinang, Malaysia
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Hamidi Abdul Aziz
Hamidi Abdul Aziz
f)
1
School of Civil Engineering, Engineering Campus, Universiti Sains Malaysia
, 14300 Nibong Tebal, P. Pinang, Malaysia
2
Solid Waste Management Cluster, Science and Engineering Research Centre, Engineering Campus, Universiti Sains Malaysia
, 14300 Nibong Tebal, Penang, Malaysia
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Sohaib K. M. Abujayyab
1,a)
Mohd Sanusi S. Ahamad
1,2,b)
Ahmad Shukri Yahya
1,c)
Siti Zubaidah Ahmad
1,d)
Mutasem Sh. Alkhasawneh
1,e)
Hamidi Abdul Aziz
1,2,f)
1
School of Civil Engineering, Engineering Campus, Universiti Sains Malaysia
, 14300 Nibong Tebal, P. Pinang, Malaysia
2
Solid Waste Management Cluster, Science and Engineering Research Centre, Engineering Campus, Universiti Sains Malaysia
, 14300 Nibong Tebal, Penang, Malaysia
AIP Conf. Proc. 1892, 130004 (2017)
Citation
Sohaib K. M. Abujayyab, Mohd Sanusi S. Ahamad, Ahmad Shukri Yahya, Siti Zubaidah Ahmad, Mutasem Sh. Alkhasawneh, Hamidi Abdul Aziz; Quantitative workflow based on NN for weighting criteria in landfill suitability mapping. AIP Conf. Proc. 16 October 2017; 1892 (1): 130004. https://doi.org/10.1063/1.5005760
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