Waste to energy spatial suitability analysis using hybrid multi-criteria machine learning approach.
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| Title: | Waste to energy spatial suitability analysis using hybrid multi-criteria machine learning approach. |
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| Authors: | Al-Ruzouq R; Civil and Environmental Engineering Department, University of Sharjah, P.O. Box 27272, Sharjah, United Arab Emirates. ralruzouq@sharjah.ac.ae.; GIS & Remote Sensing Center, Research Institute of Sciences and Engineering, University of Sharjah, P.O. Box 27272, Sharjah, United Arab Emirates. ralruzouq@sharjah.ac.ae.; Sustainable Civil Infrastructure Systems Research Group, Research Institute of Sciences and Engineering, University of Sharjah, P.O. Box 27272, Sharjah, United Arab Emirates. ralruzouq@sharjah.ac.ae., Abdallah M; Civil and Environmental Engineering Department, University of Sharjah, P.O. Box 27272, Sharjah, United Arab Emirates., Shanableh A; Civil and Environmental Engineering Department, University of Sharjah, P.O. Box 27272, Sharjah, United Arab Emirates.; GIS & Remote Sensing Center, Research Institute of Sciences and Engineering, University of Sharjah, P.O. Box 27272, Sharjah, United Arab Emirates.; Sustainable Civil Infrastructure Systems Research Group, Research Institute of Sciences and Engineering, University of Sharjah, P.O. Box 27272, Sharjah, United Arab Emirates., Alani S; Civil and Environmental Engineering Department, University of Sharjah, P.O. Box 27272, Sharjah, United Arab Emirates.; Sustainable Civil Infrastructure Systems Research Group, Research Institute of Sciences and Engineering, University of Sharjah, P.O. Box 27272, Sharjah, United Arab Emirates., Obaid L; Civil and Environmental Engineering Department, University of Sharjah, P.O. Box 27272, Sharjah, United Arab Emirates.; Sustainable Civil Infrastructure Systems Research Group, Research Institute of Sciences and Engineering, University of Sharjah, P.O. Box 27272, Sharjah, United Arab Emirates., Gibril MBA; GIS & Remote Sensing Center, Research Institute of Sciences and Engineering, University of Sharjah, P.O. Box 27272, Sharjah, United Arab Emirates. |
| Source: | Environmental science and pollution research international [Environ Sci Pollut Res Int] 2022 Jan; Vol. 29 (2), pp. 2613-2628. Date of Electronic Publication: 2021 Aug 10. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Springer Country of Publication: Germany NLM ID: 9441769 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1614-7499 (Electronic) Linking ISSN: 09441344 NLM ISO Abbreviation: Environ Sci Pollut Res Int Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1614-7499 |
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| DOI: | 10.1007/s11356-021-15289-0 |
