A Novel Evolutionary Deep Learning Approach for PM2.5 Prediction Using Remote Sensing and Spatial–Temporal Data: A Case Study of Tehran
| datacite.relatedItem.firstPage | 42 | |
| datacite.relatedItem.issue | 2 | |
| datacite.relatedItem.relatedIdentifierType | ISSN | |
| datacite.relatedItem.relatedItemIdentifier | 2220-9964 | |
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| datacite.relatedItem.title | IJGI | |
| datacite.relatedItem.volume | 14 | |
| dc.contributor.author | Mehrdad Kaveh | |
| dc.contributor.author | Mohammad Saadi Mesgari | |
| dc.contributor.author | Masoud Kaveh | |
| dc.date.accessioned | 2025-05-14T17:12:30Z | |
| dc.date.available | 2025-05-14T17:12:30Z | |
| dc.date.issued | 2025 | |
| dc.identifier.doi | https://doi.org/10.3390/ijgi14020042 | |
| dc.identifier.other | jz000158-0122 | |
| dc.identifier.uri | https://tustorage.ulb.tu-darmstadt.de/handle/tustorage/33272 | |
| dc.publisher | MDPI AG | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.subject.ddc | 550 | |
| dc.title | A Novel Evolutionary Deep Learning Approach for PM2.5 Prediction Using Remote Sensing and Spatial–Temporal Data: A Case Study of Tehran | |
| dc.type | Article | |
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