Changes
On January 3, 2025 at 1:08:17 AM UTC, admin:
-
Changed value of field
doi_status
toTrue
in Cluster-based ensemble learning for wind power modeling with meteorological wind data -
Changed value of field
doi_date_published
to2025-01-03
in Cluster-based ensemble learning for wind power modeling with meteorological wind data -
Added resource Original Metadata to Cluster-based ensemble learning for wind power modeling with meteorological wind data
f | 1 | { | f | 1 | { |
2 | "access_rights": "", | 2 | "access_rights": "", | ||
3 | "author": "Hao Chen", | 3 | "author": "Hao Chen", | ||
4 | "author_email": "", | 4 | "author_email": "", | ||
5 | "citation": [], | 5 | "citation": [], | ||
6 | "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700", | 6 | "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700", | ||
7 | "defined_in": "https://doi.org/10.48550/arXiv.2204.00646", | 7 | "defined_in": "https://doi.org/10.48550/arXiv.2204.00646", | ||
8 | "doi": "10.57702/ymf59kvt", | 8 | "doi": "10.57702/ymf59kvt", | ||
n | 9 | "doi_date_published": null, | n | 9 | "doi_date_published": "2025-01-03", |
10 | "doi_publisher": "TIB", | 10 | "doi_publisher": "TIB", | ||
n | 11 | "doi_status": false, | n | 11 | "doi_status": true, |
12 | "domain": "https://service.tib.eu/ldmservice", | 12 | "domain": "https://service.tib.eu/ldmservice", | ||
13 | "groups": [ | 13 | "groups": [ | ||
14 | { | 14 | { | ||
15 | "description": "", | 15 | "description": "", | ||
16 | "display_name": "Clustering", | 16 | "display_name": "Clustering", | ||
17 | "id": "20ed4da8-7a35-429f-92a0-c7f30914289f", | 17 | "id": "20ed4da8-7a35-429f-92a0-c7f30914289f", | ||
18 | "image_display_url": "", | 18 | "image_display_url": "", | ||
19 | "name": "clustering", | 19 | "name": "clustering", | ||
20 | "title": "Clustering" | 20 | "title": "Clustering" | ||
21 | }, | 21 | }, | ||
22 | { | 22 | { | ||
23 | "description": "", | 23 | "description": "", | ||
24 | "display_name": "Ensemble Learning", | 24 | "display_name": "Ensemble Learning", | ||
25 | "id": "d7380ff4-62e2-42c7-87b7-337c4cd84446", | 25 | "id": "d7380ff4-62e2-42c7-87b7-337c4cd84446", | ||
26 | "image_display_url": "", | 26 | "image_display_url": "", | ||
27 | "name": "ensemble-learning", | 27 | "name": "ensemble-learning", | ||
28 | "title": "Ensemble Learning" | 28 | "title": "Ensemble Learning" | ||
29 | } | 29 | } | ||
30 | ], | 30 | ], | ||
31 | "id": "316ecf87-b400-4e34-84c9-288e54b7b8d9", | 31 | "id": "316ecf87-b400-4e34-84c9-288e54b7b8d9", | ||
32 | "isopen": false, | 32 | "isopen": false, | ||
33 | "landing_page": "", | 33 | "landing_page": "", | ||
34 | "license_title": null, | 34 | "license_title": null, | ||
35 | "link_orkg": "", | 35 | "link_orkg": "", | ||
36 | "metadata_created": "2025-01-03T01:08:15.689708", | 36 | "metadata_created": "2025-01-03T01:08:15.689708", | ||
n | 37 | "metadata_modified": "2025-01-03T01:08:15.689714", | n | 37 | "metadata_modified": "2025-01-03T01:08:16.444695", |
38 | "name": | 38 | "name": | ||
39 | emble-learning-for-wind-power-modeling-with-meteorological-wind-data", | 39 | emble-learning-for-wind-power-modeling-with-meteorological-wind-data", | ||
40 | "notes": "Optimal implementation and monitoring of wind energy | 40 | "notes": "Optimal implementation and monitoring of wind energy | ||
41 | generation hinge on reliable power modeling that is vital for | 41 | generation hinge on reliable power modeling that is vital for | ||
42 | understanding turbine control, farm operational optimization, and grid | 42 | understanding turbine control, farm operational optimization, and grid | ||
43 | load balance.", | 43 | load balance.", | ||
n | 44 | "num_resources": 0, | n | 44 | "num_resources": 1, |
45 | "num_tags": 4, | 45 | "num_tags": 4, | ||
46 | "organization": { | 46 | "organization": { | ||
47 | "approval_status": "approved", | 47 | "approval_status": "approved", | ||
48 | "created": "2024-11-25T12:11:38.292601", | 48 | "created": "2024-11-25T12:11:38.292601", | ||
49 | "description": "", | 49 | "description": "", | ||
50 | "id": "079d46db-32df-4b48-91f3-0a8bc8f69559", | 50 | "id": "079d46db-32df-4b48-91f3-0a8bc8f69559", | ||
51 | "image_url": "", | 51 | "image_url": "", | ||
52 | "is_organization": true, | 52 | "is_organization": true, | ||
53 | "name": "no-organization", | 53 | "name": "no-organization", | ||
54 | "state": "active", | 54 | "state": "active", | ||
55 | "title": "No Organization", | 55 | "title": "No Organization", | ||
56 | "type": "organization" | 56 | "type": "organization" | ||
57 | }, | 57 | }, | ||
58 | "owner_org": "079d46db-32df-4b48-91f3-0a8bc8f69559", | 58 | "owner_org": "079d46db-32df-4b48-91f3-0a8bc8f69559", | ||
59 | "private": false, | 59 | "private": false, | ||
60 | "relationships_as_object": [], | 60 | "relationships_as_object": [], | ||
61 | "relationships_as_subject": [], | 61 | "relationships_as_subject": [], | ||
t | 62 | "resources": [], | t | 62 | "resources": [ |
63 | { | ||||
64 | "cache_last_updated": null, | ||||
65 | "cache_url": null, | ||||
66 | "created": "2025-01-03T00:16:35", | ||||
67 | "data": [ | ||||
68 | "dcterms:title", | ||||
69 | "dcterms:accessRights", | ||||
70 | "dcterms:creator", | ||||
71 | "dcterms:description", | ||||
72 | "dcterms:issued", | ||||
73 | "dcterms:language", | ||||
74 | "dcterms:identifier", | ||||
75 | "dcat:theme", | ||||
76 | "dcterms:type", | ||||
77 | "dcat:keyword", | ||||
78 | "dcat:landingPage", | ||||
79 | "dcterms:hasVersion", | ||||
80 | "dcterms:format", | ||||
81 | "mls:task", | ||||
82 | "datacite:isDescribedBy" | ||||
83 | ], | ||||
84 | "description": "The json representation of the dataset with its | ||||
85 | distributions based on DCAT.", | ||||
86 | "format": "JSON", | ||||
87 | "hash": "", | ||||
88 | "id": "84a9448d-9441-4df9-8d18-cdc4c5efd6a3", | ||||
89 | "last_modified": "2025-01-03T01:08:16.437507", | ||||
90 | "metadata_modified": "2025-01-03T01:08:16.447479", | ||||
91 | "mimetype": "application/json", | ||||
92 | "mimetype_inner": null, | ||||
93 | "name": "Original Metadata", | ||||
94 | "package_id": "316ecf87-b400-4e34-84c9-288e54b7b8d9", | ||||
95 | "position": 0, | ||||
96 | "resource_type": null, | ||||
97 | "size": 839, | ||||
98 | "state": "active", | ||||
99 | "url": | ||||
100 | resource/84a9448d-9441-4df9-8d18-cdc4c5efd6a3/download/metadata.json", | ||||
101 | "url_type": "upload" | ||||
102 | } | ||||
103 | ], | ||||
63 | "services_used_list": "", | 104 | "services_used_list": "", | ||
64 | "state": "active", | 105 | "state": "active", | ||
65 | "tags": [ | 106 | "tags": [ | ||
66 | { | 107 | { | ||
67 | "display_name": "Clustering", | 108 | "display_name": "Clustering", | ||
68 | "id": "7aa3309d-1ff8-4a9e-afce-b68ebd1363d6", | 109 | "id": "7aa3309d-1ff8-4a9e-afce-b68ebd1363d6", | ||
69 | "name": "Clustering", | 110 | "name": "Clustering", | ||
70 | "state": "active", | 111 | "state": "active", | ||
71 | "vocabulary_id": null | 112 | "vocabulary_id": null | ||
72 | }, | 113 | }, | ||
73 | { | 114 | { | ||
74 | "display_name": "Ensemble Learning", | 115 | "display_name": "Ensemble Learning", | ||
75 | "id": "cb407054-f079-4c0b-9ab8-b99a0dd87016", | 116 | "id": "cb407054-f079-4c0b-9ab8-b99a0dd87016", | ||
76 | "name": "Ensemble Learning", | 117 | "name": "Ensemble Learning", | ||
77 | "state": "active", | 118 | "state": "active", | ||
78 | "vocabulary_id": null | 119 | "vocabulary_id": null | ||
79 | }, | 120 | }, | ||
80 | { | 121 | { | ||
81 | "display_name": "Meteorological Data", | 122 | "display_name": "Meteorological Data", | ||
82 | "id": "c45c0e2c-efa1-47ad-bbc8-02184f7a70d7", | 123 | "id": "c45c0e2c-efa1-47ad-bbc8-02184f7a70d7", | ||
83 | "name": "Meteorological Data", | 124 | "name": "Meteorological Data", | ||
84 | "state": "active", | 125 | "state": "active", | ||
85 | "vocabulary_id": null | 126 | "vocabulary_id": null | ||
86 | }, | 127 | }, | ||
87 | { | 128 | { | ||
88 | "display_name": "Wind Power", | 129 | "display_name": "Wind Power", | ||
89 | "id": "232dd835-ed3d-4bc6-ace0-d4cb954a65bf", | 130 | "id": "232dd835-ed3d-4bc6-ace0-d4cb954a65bf", | ||
90 | "name": "Wind Power", | 131 | "name": "Wind Power", | ||
91 | "state": "active", | 132 | "state": "active", | ||
92 | "vocabulary_id": null | 133 | "vocabulary_id": null | ||
93 | } | 134 | } | ||
94 | ], | 135 | ], | ||
95 | "title": "Cluster-based ensemble learning for wind power modeling | 136 | "title": "Cluster-based ensemble learning for wind power modeling | ||
96 | with meteorological wind data", | 137 | with meteorological wind data", | ||
97 | "type": "dataset", | 138 | "type": "dataset", | ||
98 | "version": "" | 139 | "version": "" | ||
99 | } | 140 | } |