Performance evaluation of hospital site suitability using multilayer perceptron MLP and analytical hierarchy process AHP models in Malacca, Malaysia
This study focuses on suitable site identification for constructing a hospital in Malacca, Malaysia. Using significant environmental, topographic, and geodemographic factors, the study evaluated and compared machine learning (ML) and multicriteria decision analysis (MCDA) for hospital site suitabili...
| Main Authors: | , , , , , |
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| Format: | Article |
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Mary Ann Liebert
2022
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| Online Access: | http://psasir.upm.edu.my/id/eprint/102720/ |
| _version_ | 1848863862073327616 |
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| author | Almansi, Khaled Yousef Mohamed Shariff, Abdul Rashid Kalantar, Bahareh Abdullah, Ahmad Fikri Syed Ismail, Sharifah Norkhadijah Ueda, Naonori |
| author_facet | Almansi, Khaled Yousef Mohamed Shariff, Abdul Rashid Kalantar, Bahareh Abdullah, Ahmad Fikri Syed Ismail, Sharifah Norkhadijah Ueda, Naonori |
| author_sort | Almansi, Khaled Yousef |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | This study focuses on suitable site identification for constructing a hospital in Malacca, Malaysia. Using significant environmental, topographic, and geodemographic factors, the study evaluated and compared machine learning (ML) and multicriteria decision analysis (MCDA) for hospital site suitability mapping to discover the highest influential factors that minimize the error ratio and maximize the effectiveness of the suitability investigation. Identification of the most significant conditioning parameters that impact the choice of an appropriate hospital site was accomplished using correlation-based feature selection (CFS) with a search algorithm (greedy stepwise). To model the potential hospital site map, we utilized multilayer perceptron (MLP) and analytical hierarchy process (AHP) models. The outcome of the predicted site models was validated utilizing CFS 10-fold cross-validation, as well as ROC curve (receiver operating characteristic curve). The analysis of CFS indicated a very high correlation with R2 values of 0.99 for the MLP model. However, the ROC curve indicated a prediction accuracy of 80% for the MLP model and 83% for the AHP model. The findings revealed that the MLP model is reliable and consistent with the AHP. It is a sufficiently promising approach to the location suitability of hospitals to ensure effective planning and performance of healthcare delivery. |
| first_indexed | 2025-11-15T13:39:39Z |
| format | Article |
| id | upm-102720 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-15T13:39:39Z |
| publishDate | 2022 |
| publisher | Mary Ann Liebert |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-1027202024-06-22T13:57:04Z http://psasir.upm.edu.my/id/eprint/102720/ Performance evaluation of hospital site suitability using multilayer perceptron MLP and analytical hierarchy process AHP models in Malacca, Malaysia Almansi, Khaled Yousef Mohamed Shariff, Abdul Rashid Kalantar, Bahareh Abdullah, Ahmad Fikri Syed Ismail, Sharifah Norkhadijah Ueda, Naonori This study focuses on suitable site identification for constructing a hospital in Malacca, Malaysia. Using significant environmental, topographic, and geodemographic factors, the study evaluated and compared machine learning (ML) and multicriteria decision analysis (MCDA) for hospital site suitability mapping to discover the highest influential factors that minimize the error ratio and maximize the effectiveness of the suitability investigation. Identification of the most significant conditioning parameters that impact the choice of an appropriate hospital site was accomplished using correlation-based feature selection (CFS) with a search algorithm (greedy stepwise). To model the potential hospital site map, we utilized multilayer perceptron (MLP) and analytical hierarchy process (AHP) models. The outcome of the predicted site models was validated utilizing CFS 10-fold cross-validation, as well as ROC curve (receiver operating characteristic curve). The analysis of CFS indicated a very high correlation with R2 values of 0.99 for the MLP model. However, the ROC curve indicated a prediction accuracy of 80% for the MLP model and 83% for the AHP model. The findings revealed that the MLP model is reliable and consistent with the AHP. It is a sufficiently promising approach to the location suitability of hospitals to ensure effective planning and performance of healthcare delivery. Mary Ann Liebert 2022 Article PeerReviewed Almansi, Khaled Yousef and Mohamed Shariff, Abdul Rashid and Kalantar, Bahareh and Abdullah, Ahmad Fikri and Syed Ismail, Sharifah Norkhadijah and Ueda, Naonori (2022) Performance evaluation of hospital site suitability using multilayer perceptron MLP and analytical hierarchy process AHP models in Malacca, Malaysia. Sustainability, 14 (7). art. no. 3731. pp. 1-36. ISSN 1937-0695; ESSN: 1937-0709 https://www.mdpi.com/2071-1050/14/7/3731 10.3390/su14073731 |
| spellingShingle | Almansi, Khaled Yousef Mohamed Shariff, Abdul Rashid Kalantar, Bahareh Abdullah, Ahmad Fikri Syed Ismail, Sharifah Norkhadijah Ueda, Naonori Performance evaluation of hospital site suitability using multilayer perceptron MLP and analytical hierarchy process AHP models in Malacca, Malaysia |
| title | Performance evaluation of hospital site suitability using multilayer perceptron MLP and analytical hierarchy process AHP models in Malacca, Malaysia |
| title_full | Performance evaluation of hospital site suitability using multilayer perceptron MLP and analytical hierarchy process AHP models in Malacca, Malaysia |
| title_fullStr | Performance evaluation of hospital site suitability using multilayer perceptron MLP and analytical hierarchy process AHP models in Malacca, Malaysia |
| title_full_unstemmed | Performance evaluation of hospital site suitability using multilayer perceptron MLP and analytical hierarchy process AHP models in Malacca, Malaysia |
| title_short | Performance evaluation of hospital site suitability using multilayer perceptron MLP and analytical hierarchy process AHP models in Malacca, Malaysia |
| title_sort | performance evaluation of hospital site suitability using multilayer perceptron mlp and analytical hierarchy process ahp models in malacca, malaysia |
| url | http://psasir.upm.edu.my/id/eprint/102720/ http://psasir.upm.edu.my/id/eprint/102720/ http://psasir.upm.edu.my/id/eprint/102720/ |