131 to 140 of 236 Results
Apr 19, 2024 - Marine Forecast Dataverse
Wahyudi, Aan Johan, 2023, "Supplementary materials of POC forecast (Sunda Shelf Sea)", https://hdl.handle.net/20.500.12690/RIN/DKMABL, RIN Dataverse, V3, UNF:6:mQu2raqyMv99KVhCC56f4A== [fileUNF]
Supplementary materials of Sunda Shelf's POC forecast (SARIMA and SARIMAX) |
Apr 19, 2024 -
Supplementary materials of POC forecast (Sunda Shelf Sea)
Adobe PDF - 160.4 KB -
MD5: f0ad89bb83331732b09186354ecc921b
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Mar 21, 2024 -
Supplementary materials of POC forecast (Sunda Shelf Sea)
Tabular Data - 19.4 KB - 7 Variables, 279 Observations - UNF:6:kNFntbr3KTfNrZHmRy0KeA==
Hindcast dataset of POC of Sunda Shelf Sea |
Mar 21, 2024 -
Supplementary materials of POC forecast (Sunda Shelf Sea)
MS Word - 16.8 KB -
MD5: 5dc89dd5225166757552c3394b4ff2ab
PLS result |
Mar 21, 2024 -
Supplementary materials of POC forecast (Sunda Shelf Sea)
MS Word - 29.5 KB -
MD5: 2686e1174f79007246df633a4ed37189
Python code for generating SARIMA and SARIMAX model |
Mar 21, 2024 -
Supplementary materials of POC forecast (Sunda Shelf Sea)
MS Word - 902.3 KB -
MD5: d7dcccd0193a49e0d406989727f7a165
SARIMA and SARIMAX metric and validation |
Mar 21, 2024 -
Supplementary materials of POC forecast (Sunda Shelf Sea)
Tabular Data - 7.0 KB - 5 Variables, 98 Observations - UNF:6:OfrgnFQZ5uB3qCR7DfKCgA==
forecast data of POC using the SARIMA model |
Mar 21, 2024 -
Supplementary materials of POC forecast (Sunda Shelf Sea)
Tabular Data - 7.0 KB - 5 Variables, 98 Observations - UNF:6:8yG9hJJkOIRGIvz95kVYWw==
forecast data of POC using the SARIMAX[exog=SST] model |
Mar 21, 2024 -
Supplementary materials of POC forecast (Sunda Shelf Sea)
MS Word - 14.7 KB -
MD5: bea3a256f1e94d65ef3261884560e695
Appendix |
Jan 22, 2024 - Mikroba dan Plankton Laut Dataverse
Rachman, Arief, 2024, "RIIM3 Phytoplankton Image Dataset", https://hdl.handle.net/20.500.12690/RIN/HNTMNM, RIN Dataverse, V1
This is the ongoing phytoplankton image dataset created for RIIM 3 "Pengembangan Sistem Identifikasi Fitoplankton Perairan Indonesia dengan Menggunakan Computer Vision". The dataset will grow as more data is generated from the project. |