SPATIAL DATA MINING TOOLBOX FOR MAPPING SUITABILITY OF LANDFILL SITES USING NEURAL NETWORKS
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...
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2016
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| Online Access: | http://eprints.usm.my/37222/ http://eprints.usm.my/37222/1/%28SPATIAL_DATA_MINING_TOOLBOX%29_isprs-archives-XLII-4-W1-199-2016.pdf |
| _version_ | 1848878132718731264 |
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| author | Abujayyab, Sohaib K. M. S. Ahamad, Mohd Sanusi Yahya, Ahmad Shukri Abdul Aziz, Hamidi |
| author_facet | Abujayyab, Sohaib K. M. S. Ahamad, Mohd Sanusi Yahya, Ahmad Shukri Abdul Aziz, Hamidi |
| author_sort | Abujayyab, Sohaib K. M. |
| building | USM Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-15T17:26:29Z |
| format | Article |
| id | usm-37222 |
| institution | Universiti Sains Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T17:26:29Z |
| publishDate | 2016 |
| publisher | Copernicus Publications |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | usm-372222017-10-20T07:07:02Z http://eprints.usm.my/37222/ SPATIAL DATA MINING TOOLBOX FOR MAPPING SUITABILITY OF LANDFILL SITES USING NEURAL NETWORKS Abujayyab, Sohaib K. M. S. Ahamad, Mohd Sanusi Yahya, Ahmad Shukri Abdul Aziz, Hamidi TA1-2040 Engineering (General). Civil engineering (General) 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. Copernicus Publications 2016 Article PeerReviewed application/pdf en http://eprints.usm.my/37222/1/%28SPATIAL_DATA_MINING_TOOLBOX%29_isprs-archives-XLII-4-W1-199-2016.pdf 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 https://doi.org/10.5194/isprs-archives-XLII-4-W1-199-2016 |
| spellingShingle | TA1-2040 Engineering (General). Civil engineering (General) Abujayyab, Sohaib K. M. S. Ahamad, Mohd Sanusi Yahya, Ahmad Shukri Abdul Aziz, Hamidi SPATIAL DATA MINING TOOLBOX FOR MAPPING SUITABILITY OF LANDFILL SITES USING NEURAL NETWORKS |
| title | SPATIAL DATA MINING TOOLBOX FOR MAPPING SUITABILITY OF LANDFILL SITES USING NEURAL NETWORKS |
| title_full | SPATIAL DATA MINING TOOLBOX FOR MAPPING SUITABILITY OF LANDFILL SITES USING NEURAL NETWORKS |
| title_fullStr | SPATIAL DATA MINING TOOLBOX FOR MAPPING SUITABILITY OF LANDFILL SITES USING NEURAL NETWORKS |
| title_full_unstemmed | SPATIAL DATA MINING TOOLBOX FOR MAPPING SUITABILITY OF LANDFILL SITES USING NEURAL NETWORKS |
| title_short | SPATIAL DATA MINING TOOLBOX FOR MAPPING SUITABILITY OF LANDFILL SITES USING NEURAL NETWORKS |
| title_sort | spatial data mining toolbox for mapping suitability of landfill sites using neural networks |
| topic | TA1-2040 Engineering (General). Civil engineering (General) |
| url | http://eprints.usm.my/37222/ http://eprints.usm.my/37222/ http://eprints.usm.my/37222/1/%28SPATIAL_DATA_MINING_TOOLBOX%29_isprs-archives-XLII-4-W1-199-2016.pdf |