SPATIAL DATA MINING TOOLBOX FOR MAPPING SUITABILITY OF LANDFILL SITES USING NEURAL NETWORKS

Abujayyab, Sohaib K. M. and S. Ahamad, Mohd Sanusi and Yahya, Ahmad Shukri and Abdul Aziz, Hamidi (2016) SPATIAL DATA MINING TOOLBOX FOR MAPPING SUITABILITY OF LANDFILL SITES USING NEURAL NETWORKS. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-4 (W1). pp. 199-208. ISSN 1682-1750

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Abstract

Mapping the suitability of landfill sites is a complex field and is involved with multidiscipline. The purpose of this research is to create an ArcGIS spatial data mining toolbox for mapping the suitability of landfill sites at a regional scale using neural networks. The toolbox is constructed from six sub-tools to prepare, train, and process data. The employment of the toolbox is straightforward. The multilayer perceptron (MLP) neural networks structure with a backpropagation learning algorithm is used. The dataset is mined from the north states in Malaysia. A total of 14 criteria are utilized to build the training dataset. The toolbox provides a platform for decision makers to implement neural networks for mapping the suitability of landfill sites in the ArcGIS environment. The result shows the ability of the toolbox to produce suitability maps for landfill sites.

Item Type:	Article
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) > TA1-2040 Engineering (General). Civil engineering (General)
Divisions:	Kampus Kejuruteraan (Engineering Campus) > Pusat Pengajian Kejuruteraan Awam (School of Civil Engineering) > Article
Depositing User:	Mr Noorazilan Noordin
Date Deposited:	20 Oct 2017 07:07
Last Modified:	20 Oct 2017 07:07
URI:	http://eprints.usm.my/id/eprint/37222

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