Cambios
En el instante 30 de octubre de 2025, 2:06:55 UTC,
albertogarob:
-
Eliminadas las siguientes etiquetas de Redes Neuronales para Predecir Datos Climatológicos
-
Añadidas las siguientes etiquetas de Redes Neuronales para Predecir Datos Climatológicos
- analisis-geoespacial
- prediccion-climatica
- formula-haversine
- servicio-meteorologico-nacional
- prediccion-de-precipitacion
- mexico
- aprendizaje-automatico
- correlacion-de-estaciones
- interpolacion-espacial
- 2025
- evaporacion
- estaciones-meteorologicas
- perceptron-multicapa
- variables-meteorologicas
- meteorologia
- datos-climatologicos
-
Añadido campo
Año
con valor2025
a Redes Neuronales para Predecir Datos Climatológicos
| f | 1 | { | f | 1 | { |
| 2 | "author": "S. Ivvan Valdez Pe\u00f1a, Zaira Mart\u00ednez Vargas, | 2 | "author": "S. Ivvan Valdez Pe\u00f1a, Zaira Mart\u00ednez Vargas, | ||
| 3 | Jorge Paredes Tavares", | 3 | Jorge Paredes Tavares", | ||
| 4 | "author_email": null, | 4 | "author_email": null, | ||
| 5 | "creator_user_id": "a3da3ec9-3fd4-47a4-8d04-0a90b09614e0", | 5 | "creator_user_id": "a3da3ec9-3fd4-47a4-8d04-0a90b09614e0", | ||
| 6 | "extras": [ | 6 | "extras": [ | ||
| 7 | { | 7 | { | ||
| n | n | 8 | "key": "A\u00f1o", | ||
| 9 | "value": "2025" | ||||
| 10 | }, | ||||
| 11 | { | ||||
| 8 | "key": "Identificador hash", | 12 | "key": "Identificador hash", | ||
| 9 | "value": "89d9c71b34ea" | 13 | "value": "89d9c71b34ea" | ||
| 10 | }, | 14 | }, | ||
| 11 | { | 15 | { | ||
| 12 | "key": "Instituciones", | 16 | "key": "Instituciones", | ||
| 13 | "value": "SECIHTI-CentroGeo, Universidad de Guadalajara" | 17 | "value": "SECIHTI-CentroGeo, Universidad de Guadalajara" | ||
| 14 | }, | 18 | }, | ||
| 15 | { | 19 | { | ||
| 16 | "key": "Tipo", | 20 | "key": "Tipo", | ||
| 17 | "value": "Art\u00edculo en l\u00ednea" | 21 | "value": "Art\u00edculo en l\u00ednea" | ||
| 18 | }, | 22 | }, | ||
| 19 | { | 23 | { | ||
| 20 | "key": "URL", | 24 | "key": "URL", | ||
| 21 | "value": | 25 | "value": | ||
| 22 | servatoriogeo.mx/redes-neuronales-para-predecir-datos-climatologicos/" | 26 | servatoriogeo.mx/redes-neuronales-para-predecir-datos-climatologicos/" | ||
| 23 | } | 27 | } | ||
| 24 | ], | 28 | ], | ||
| 25 | "groups": [ | 29 | "groups": [ | ||
| 26 | { | 30 | { | ||
| n | 27 | "description": "", | n | 31 | "description": "Este grupo re\u00fane los art\u00edculos de |
| 32 | divulgaci\u00f3n publicados por el Observatorio Metropolitano del | ||||
| 33 | CentroGeo. Cada art\u00edculo presenta, en un lenguaje accesible y con | ||||
| 34 | enfoque metropolitano, los principales hallazgos, metodolog\u00edas y | ||||
| 35 | aplicaciones de los proyectos de investigaci\u00f3n desarrollados por | ||||
| 36 | el observatorio. Los contenidos est\u00e1n hospedados en el portal web | ||||
| 37 | del Observatorio Metropolitano y buscan acercar el conocimiento | ||||
| 38 | cient\u00edfico y t\u00e9cnico a la sociedad, fomentando la | ||||
| 39 | comprensi\u00f3n de los fen\u00f3menos urbanos y territoriales desde | ||||
| 40 | una perspectiva interdisciplinaria.", | ||||
| 28 | "display_name": "Art\u00edculos en l\u00ednea", | 41 | "display_name": "Art\u00edculos en l\u00ednea", | ||
| 29 | "id": "8659310a-f66e-46e8-b1e5-3d7e04acd171", | 42 | "id": "8659310a-f66e-46e8-b1e5-3d7e04acd171", | ||
| 30 | "image_display_url": "", | 43 | "image_display_url": "", | ||
| 31 | "name": "articulos-en-linea", | 44 | "name": "articulos-en-linea", | ||
| 32 | "title": "Art\u00edculos en l\u00ednea" | 45 | "title": "Art\u00edculos en l\u00ednea" | ||
| 33 | } | 46 | } | ||
| 34 | ], | 47 | ], | ||
| 35 | "id": "b278578c-6860-441d-901e-00e251bb1a29", | 48 | "id": "b278578c-6860-441d-901e-00e251bb1a29", | ||
| 36 | "isopen": false, | 49 | "isopen": false, | ||
| 37 | "license_id": null, | 50 | "license_id": null, | ||
| 38 | "license_title": null, | 51 | "license_title": null, | ||
| 39 | "maintainer": null, | 52 | "maintainer": null, | ||
| 40 | "maintainer_email": null, | 53 | "maintainer_email": null, | ||
| 41 | "metadata_created": "2025-10-24T00:46:46.716371", | 54 | "metadata_created": "2025-10-24T00:46:46.716371", | ||
| n | 42 | "metadata_modified": "2025-10-24T00:46:47.358127", | n | 55 | "metadata_modified": "2025-10-30T02:06:55.672239", |
| 43 | "name": "89d9c71b34ea", | 56 | "name": "89d9c71b34ea", | ||
| 44 | "notes": "El objetivo de este trabajo fue utilizar una red neuronal | 57 | "notes": "El objetivo de este trabajo fue utilizar una red neuronal | ||
| 45 | para poder predecir datos de precipitaci\u00f3n a partir de datos | 58 | para poder predecir datos de precipitaci\u00f3n a partir de datos | ||
| 46 | conocidos y de las estaciones m\u00e1s cercanas utilizando una base de | 59 | conocidos y de las estaciones m\u00e1s cercanas utilizando una base de | ||
| 47 | datos tomada de la p\u00e1gina de CONAGUA del gobierno de | 60 | datos tomada de la p\u00e1gina de CONAGUA del gobierno de | ||
| 48 | M\u00e9xico.", | 61 | M\u00e9xico.", | ||
| 49 | "num_resources": 1, | 62 | "num_resources": 1, | ||
| n | 50 | "num_tags": 29, | n | 63 | "num_tags": 30, |
| 51 | "organization": { | 64 | "organization": { | ||
| 52 | "approval_status": "approved", | 65 | "approval_status": "approved", | ||
| 53 | "created": "2022-05-19T00:10:30.480393", | 66 | "created": "2022-05-19T00:10:30.480393", | ||
| 54 | "description": "Observatorio Metropolitano CentroGeo", | 67 | "description": "Observatorio Metropolitano CentroGeo", | ||
| 55 | "id": "b3b3a79d-748a-4464-9471-732b6c74ec53", | 68 | "id": "b3b3a79d-748a-4464-9471-732b6c74ec53", | ||
| 56 | "image_url": | 69 | "image_url": | ||
| 57 | "2022-05-19-001030.456616FullColor1280x1024LogoOnly.png", | 70 | "2022-05-19-001030.456616FullColor1280x1024LogoOnly.png", | ||
| 58 | "is_organization": true, | 71 | "is_organization": true, | ||
| 59 | "name": "observatorio-metropolitano-centrogeo", | 72 | "name": "observatorio-metropolitano-centrogeo", | ||
| 60 | "state": "active", | 73 | "state": "active", | ||
| 61 | "title": "Observatorio Metropolitano CentroGeo", | 74 | "title": "Observatorio Metropolitano CentroGeo", | ||
| 62 | "type": "organization" | 75 | "type": "organization" | ||
| 63 | }, | 76 | }, | ||
| 64 | "owner_org": "b3b3a79d-748a-4464-9471-732b6c74ec53", | 77 | "owner_org": "b3b3a79d-748a-4464-9471-732b6c74ec53", | ||
| 65 | "private": false, | 78 | "private": false, | ||
| 66 | "relationships_as_object": [], | 79 | "relationships_as_object": [], | ||
| 67 | "relationships_as_subject": [], | 80 | "relationships_as_subject": [], | ||
| 68 | "resources": [ | 81 | "resources": [ | ||
| 69 | { | 82 | { | ||
| 70 | "cache_last_updated": null, | 83 | "cache_last_updated": null, | ||
| 71 | "cache_url": null, | 84 | "cache_url": null, | ||
| 72 | "created": "2025-10-24T00:46:47.424604", | 85 | "created": "2025-10-24T00:46:47.424604", | ||
| 73 | "datastore_active": false, | 86 | "datastore_active": false, | ||
| 74 | "description": "El objetivo de este trabajo fue utilizar una red | 87 | "description": "El objetivo de este trabajo fue utilizar una red | ||
| 75 | neuronal para poder predecir datos de precipitaci\u00f3n a partir de | 88 | neuronal para poder predecir datos de precipitaci\u00f3n a partir de | ||
| 76 | datos conocidos y de las estaciones m\u00e1s cercanas utilizando una | 89 | datos conocidos y de las estaciones m\u00e1s cercanas utilizando una | ||
| 77 | base de datos tomada de la p\u00e1gina de CONAGUA del gobierno de | 90 | base de datos tomada de la p\u00e1gina de CONAGUA del gobierno de | ||
| 78 | M\u00e9xico.", | 91 | M\u00e9xico.", | ||
| 79 | "format": "HTML", | 92 | "format": "HTML", | ||
| 80 | "hash": "", | 93 | "hash": "", | ||
| 81 | "id": "137cc315-0af4-45a7-81b7-e67c2a7bbe7e", | 94 | "id": "137cc315-0af4-45a7-81b7-e67c2a7bbe7e", | ||
| 82 | "last_modified": null, | 95 | "last_modified": null, | ||
| n | 83 | "metadata_modified": "2025-10-24T00:46:47.362303", | n | 96 | "metadata_modified": "2025-10-30T02:06:55.676344", |
| 84 | "mimetype": null, | 97 | "mimetype": null, | ||
| 85 | "mimetype_inner": null, | 98 | "mimetype_inner": null, | ||
| 86 | "name": "Redes Neuronales para Predecir Datos | 99 | "name": "Redes Neuronales para Predecir Datos | ||
| 87 | Climatol\u00f3gicos", | 100 | Climatol\u00f3gicos", | ||
| 88 | "package_id": "b278578c-6860-441d-901e-00e251bb1a29", | 101 | "package_id": "b278578c-6860-441d-901e-00e251bb1a29", | ||
| 89 | "position": 0, | 102 | "position": 0, | ||
| 90 | "resource_type": null, | 103 | "resource_type": null, | ||
| 91 | "size": null, | 104 | "size": null, | ||
| 92 | "state": "active", | 105 | "state": "active", | ||
| 93 | "url": | 106 | "url": | ||
| 94 | ervatoriogeo.mx/redes-neuronales-para-predecir-datos-climatologicos/", | 107 | ervatoriogeo.mx/redes-neuronales-para-predecir-datos-climatologicos/", | ||
| 95 | "url_type": null | 108 | "url_type": null | ||
| 96 | } | 109 | } | ||
| 97 | ], | 110 | ], | ||
| 98 | "state": "active", | 111 | "state": "active", | ||
| 99 | "tags": [ | 112 | "tags": [ | ||
| 100 | { | 113 | { | ||
| n | n | 114 | "display_name": "2025", | ||
| 115 | "id": "61321a03-ac7d-45bd-b420-27e6d90d1e48", | ||||
| 116 | "name": "2025", | ||||
| 117 | "state": "active", | ||||
| 118 | "vocabulary_id": null | ||||
| 119 | }, | ||||
| 120 | { | ||||
| 101 | "display_name": "aguascalientes", | 121 | "display_name": "aguascalientes", | ||
| 102 | "id": "a36b5bcd-69a1-4de5-8528-be05fb2ca9fb", | 122 | "id": "a36b5bcd-69a1-4de5-8528-be05fb2ca9fb", | ||
| 103 | "name": "aguascalientes", | 123 | "name": "aguascalientes", | ||
| 104 | "state": "active", | 124 | "state": "active", | ||
| 105 | "vocabulary_id": null | 125 | "vocabulary_id": null | ||
| 106 | }, | 126 | }, | ||
| 107 | { | 127 | { | ||
| n | 108 | "display_name": "anlisis-geoespacial", | n | 128 | "display_name": "analisis-geoespacial", |
| 109 | "id": "a11d06ec-2054-48c8-956c-62b978c283aa", | 129 | "id": "898844f4-0c8d-43f5-b329-6b1a46c12c21", | ||
| 110 | "name": "anlisis-geoespacial", | 130 | "name": "analisis-geoespacial", | ||
| 111 | "state": "active", | 131 | "state": "active", | ||
| 112 | "vocabulary_id": null | 132 | "vocabulary_id": null | ||
| 113 | }, | 133 | }, | ||
| 114 | { | 134 | { | ||
| n | 115 | "display_name": "aprendizaje-automtico", | n | 135 | "display_name": "aprendizaje-automatico", |
| 116 | "id": "afa7293e-8d57-46ae-b963-5b051eaea287", | 136 | "id": "3bdbc672-9821-4f01-93a4-f3afea49676e", | ||
| 117 | "name": "aprendizaje-automtico", | 137 | "name": "aprendizaje-automatico", | ||
| 118 | "state": "active", | 138 | "state": "active", | ||
| 119 | "vocabulary_id": null | 139 | "vocabulary_id": null | ||
| 120 | }, | 140 | }, | ||
| 121 | { | 141 | { | ||
| 122 | "display_name": "clima", | 142 | "display_name": "clima", | ||
| 123 | "id": "9276fd7f-8824-4639-abab-655afe836282", | 143 | "id": "9276fd7f-8824-4639-abab-655afe836282", | ||
| 124 | "name": "clima", | 144 | "name": "clima", | ||
| 125 | "state": "active", | 145 | "state": "active", | ||
| 126 | "vocabulary_id": null | 146 | "vocabulary_id": null | ||
| 127 | }, | 147 | }, | ||
| 128 | { | 148 | { | ||
| 129 | "display_name": "conagua", | 149 | "display_name": "conagua", | ||
| 130 | "id": "fb3ebc63-06c7-4772-a38c-d13e40214618", | 150 | "id": "fb3ebc63-06c7-4772-a38c-d13e40214618", | ||
| 131 | "name": "conagua", | 151 | "name": "conagua", | ||
| 132 | "state": "active", | 152 | "state": "active", | ||
| 133 | "vocabulary_id": null | 153 | "vocabulary_id": null | ||
| 134 | }, | 154 | }, | ||
| 135 | { | 155 | { | ||
| n | 136 | "display_name": "correlacin-de-estaciones", | n | 156 | "display_name": "correlacion-de-estaciones", |
| 137 | "id": "9718312b-3195-4846-944c-7137fddce97a", | 157 | "id": "c1693580-81d0-4def-8443-4ae1c77df44a", | ||
| 138 | "name": "correlacin-de-estaciones", | 158 | "name": "correlacion-de-estaciones", | ||
| 139 | "state": "active", | 159 | "state": "active", | ||
| 140 | "vocabulary_id": null | 160 | "vocabulary_id": null | ||
| 141 | }, | 161 | }, | ||
| 142 | { | 162 | { | ||
| n | 143 | "display_name": "datos-climatolgicos", | n | 163 | "display_name": "datos-climatologicos", |
| 144 | "id": "67608a55-1f63-49ef-8b8d-41dc7993e020", | 164 | "id": "55930644-9738-4f62-838e-8fa84d0df2d1", | ||
| 145 | "name": "datos-climatolgicos", | 165 | "name": "datos-climatologicos", | ||
| 146 | "state": "active", | 166 | "state": "active", | ||
| 147 | "vocabulary_id": null | 167 | "vocabulary_id": null | ||
| 148 | }, | 168 | }, | ||
| 149 | { | 169 | { | ||
| n | 150 | "display_name": "estaciones-meteorolgicas", | n | 170 | "display_name": "estaciones-meteorologicas", |
| 151 | "id": "e157c629-041d-4df0-a003-db679e61287f", | 171 | "id": "0b3b281b-ee7a-4a2a-9caf-ab96845ca004", | ||
| 152 | "name": "estaciones-meteorolgicas", | 172 | "name": "estaciones-meteorologicas", | ||
| 153 | "state": "active", | 173 | "state": "active", | ||
| 154 | "vocabulary_id": null | 174 | "vocabulary_id": null | ||
| 155 | }, | 175 | }, | ||
| 156 | { | 176 | { | ||
| n | 157 | "display_name": "evaporacin", | n | 177 | "display_name": "evaporacion", |
| 158 | "id": "ae55e90f-7373-47c4-be6e-0593d9087819", | 178 | "id": "9beffcc6-d021-451f-812f-a72287b6cb1f", | ||
| 159 | "name": "evaporacin", | 179 | "name": "evaporacion", | ||
| 160 | "state": "active", | 180 | "state": "active", | ||
| 161 | "vocabulary_id": null | 181 | "vocabulary_id": null | ||
| 162 | }, | 182 | }, | ||
| 163 | { | 183 | { | ||
| n | 164 | "display_name": "frmula-haversine", | n | 184 | "display_name": "formula-haversine", |
| 165 | "id": "8d199c1f-bc62-493b-a981-da14ffa27f1d", | 185 | "id": "efbfdbb4-67f8-4fcd-9b42-4c89e13e5fad", | ||
| 166 | "name": "frmula-haversine", | 186 | "name": "formula-haversine", | ||
| 167 | "state": "active", | 187 | "state": "active", | ||
| 168 | "vocabulary_id": null | 188 | "vocabulary_id": null | ||
| 169 | }, | 189 | }, | ||
| 170 | { | 190 | { | ||
| 171 | "display_name": "humedad", | 191 | "display_name": "humedad", | ||
| 172 | "id": "4814f0f6-1b5d-47ac-b454-2752ef5bb711", | 192 | "id": "4814f0f6-1b5d-47ac-b454-2752ef5bb711", | ||
| 173 | "name": "humedad", | 193 | "name": "humedad", | ||
| 174 | "state": "active", | 194 | "state": "active", | ||
| 175 | "vocabulary_id": null | 195 | "vocabulary_id": null | ||
| 176 | }, | 196 | }, | ||
| 177 | { | 197 | { | ||
| 178 | "display_name": "inteligencia-artificial", | 198 | "display_name": "inteligencia-artificial", | ||
| 179 | "id": "77af2445-0e8a-40c2-bb38-f28434e2257b", | 199 | "id": "77af2445-0e8a-40c2-bb38-f28434e2257b", | ||
| 180 | "name": "inteligencia-artificial", | 200 | "name": "inteligencia-artificial", | ||
| 181 | "state": "active", | 201 | "state": "active", | ||
| 182 | "vocabulary_id": null | 202 | "vocabulary_id": null | ||
| 183 | }, | 203 | }, | ||
| 184 | { | 204 | { | ||
| n | 185 | "display_name": "interpolacin-espacial", | n | 205 | "display_name": "interpolacion-espacial", |
| 186 | "id": "efc44fc1-3059-476d-8f5e-3b8f60d7f3af", | 206 | "id": "123e0d3b-9017-43bb-af94-2e79ec3707b5", | ||
| 187 | "name": "interpolacin-espacial", | 207 | "name": "interpolacion-espacial", | ||
| 188 | "state": "active", | 208 | "state": "active", | ||
| 189 | "vocabulary_id": null | 209 | "vocabulary_id": null | ||
| 190 | }, | 210 | }, | ||
| 191 | { | 211 | { | ||
| 192 | "display_name": "jalisco", | 212 | "display_name": "jalisco", | ||
| 193 | "id": "29f4de33-d407-4245-92f1-c4e7ac6a143e", | 213 | "id": "29f4de33-d407-4245-92f1-c4e7ac6a143e", | ||
| 194 | "name": "jalisco", | 214 | "name": "jalisco", | ||
| 195 | "state": "active", | 215 | "state": "active", | ||
| 196 | "vocabulary_id": null | 216 | "vocabulary_id": null | ||
| 197 | }, | 217 | }, | ||
| 198 | { | 218 | { | ||
| 199 | "display_name": "jparedes", | 219 | "display_name": "jparedes", | ||
| 200 | "id": "45de6aed-42af-4ad7-8cc0-166ea484921e", | 220 | "id": "45de6aed-42af-4ad7-8cc0-166ea484921e", | ||
| 201 | "name": "jparedes", | 221 | "name": "jparedes", | ||
| 202 | "state": "active", | 222 | "state": "active", | ||
| 203 | "vocabulary_id": null | 223 | "vocabulary_id": null | ||
| 204 | }, | 224 | }, | ||
| 205 | { | 225 | { | ||
| 206 | "display_name": "limpieza-de-datos", | 226 | "display_name": "limpieza-de-datos", | ||
| 207 | "id": "083b93c8-953d-4310-aa11-e4806dabb6fb", | 227 | "id": "083b93c8-953d-4310-aa11-e4806dabb6fb", | ||
| 208 | "name": "limpieza-de-datos", | 228 | "name": "limpieza-de-datos", | ||
| 209 | "state": "active", | 229 | "state": "active", | ||
| 210 | "vocabulary_id": null | 230 | "vocabulary_id": null | ||
| 211 | }, | 231 | }, | ||
| 212 | { | 232 | { | ||
| 213 | "display_name": "lluvia", | 233 | "display_name": "lluvia", | ||
| 214 | "id": "05b4b9af-4c43-430f-a372-1b396f9ec064", | 234 | "id": "05b4b9af-4c43-430f-a372-1b396f9ec064", | ||
| 215 | "name": "lluvia", | 235 | "name": "lluvia", | ||
| 216 | "state": "active", | 236 | "state": "active", | ||
| 217 | "vocabulary_id": null | 237 | "vocabulary_id": null | ||
| 218 | }, | 238 | }, | ||
| 219 | { | 239 | { | ||
| n | 220 | "display_name": "meteorologa", | n | 240 | "display_name": "meteorologia", |
| 221 | "id": "a678e40a-89bf-42cb-bad4-c326d3cef5a0", | 241 | "id": "814fe98e-d3cd-48ec-b541-83f501e9f91b", | ||
| 222 | "name": "meteorologa", | 242 | "name": "meteorologia", | ||
| 243 | "state": "active", | ||||
| 244 | "vocabulary_id": null | ||||
| 245 | }, | ||||
| 246 | { | ||||
| 247 | "display_name": "mexico", | ||||
| 248 | "id": "913563c5-3f76-4869-ba30-05eff20c41f8", | ||||
| 249 | "name": "mexico", | ||||
| 223 | "state": "active", | 250 | "state": "active", | ||
| 224 | "vocabulary_id": null | 251 | "vocabulary_id": null | ||
| 225 | }, | 252 | }, | ||
| 226 | { | 253 | { | ||
| 227 | "display_name": "modelado-predictivo", | 254 | "display_name": "modelado-predictivo", | ||
| 228 | "id": "38a9b165-488c-4bf7-b0df-a466f5d38683", | 255 | "id": "38a9b165-488c-4bf7-b0df-a466f5d38683", | ||
| 229 | "name": "modelado-predictivo", | 256 | "name": "modelado-predictivo", | ||
| 230 | "state": "active", | 257 | "state": "active", | ||
| 231 | "vocabulary_id": null | 258 | "vocabulary_id": null | ||
| 232 | }, | 259 | }, | ||
| 233 | { | 260 | { | ||
| n | 234 | "display_name": "mxico", | n | ||
| 235 | "id": "2b9cf2e8-e723-48af-aee0-cc6a315658d7", | ||||
| 236 | "name": "mxico", | ||||
| 237 | "state": "active", | ||||
| 238 | "vocabulary_id": null | ||||
| 239 | }, | ||||
| 240 | { | ||||
| 241 | "display_name": "perceptrn-multicapa", | 261 | "display_name": "perceptron-multicapa", | ||
| 242 | "id": "4b967702-18d4-4bfc-9f25-bd7140db7857", | 262 | "id": "19ef4b44-20dc-4a03-aa95-e4ddc4ffb1b3", | ||
| 243 | "name": "perceptrn-multicapa", | 263 | "name": "perceptron-multicapa", | ||
| 244 | "state": "active", | 264 | "state": "active", | ||
| 245 | "vocabulary_id": null | 265 | "vocabulary_id": null | ||
| 246 | }, | 266 | }, | ||
| 247 | { | 267 | { | ||
| n | 248 | "display_name": "prediccin-climtica", | n | 268 | "display_name": "prediccion-climatica", |
| 249 | "id": "318bc2b8-4a79-40c8-8717-aca9a4215379", | 269 | "id": "6be055e1-b8ee-4b6e-a14b-4d4a74eacf29", | ||
| 250 | "name": "prediccin-climtica", | 270 | "name": "prediccion-climatica", | ||
| 251 | "state": "active", | 271 | "state": "active", | ||
| 252 | "vocabulary_id": null | 272 | "vocabulary_id": null | ||
| 253 | }, | 273 | }, | ||
| 254 | { | 274 | { | ||
| n | 255 | "display_name": "prediccin-de-precipitacin", | n | 275 | "display_name": "prediccion-de-precipitacion", |
| 256 | "id": "f57be693-3c51-4d39-bec4-4cbdf020aa32", | 276 | "id": "6a5846db-e319-44a1-944f-22aae84b3928", | ||
| 257 | "name": "prediccin-de-precipitacin", | 277 | "name": "prediccion-de-precipitacion", | ||
| 258 | "state": "active", | 278 | "state": "active", | ||
| 259 | "vocabulary_id": null | 279 | "vocabulary_id": null | ||
| 260 | }, | 280 | }, | ||
| 261 | { | 281 | { | ||
| 262 | "display_name": "redes-neuronales-artificiales", | 282 | "display_name": "redes-neuronales-artificiales", | ||
| 263 | "id": "7ace81a9-29b7-431c-bd26-442ba197568a", | 283 | "id": "7ace81a9-29b7-431c-bd26-442ba197568a", | ||
| 264 | "name": "redes-neuronales-artificiales", | 284 | "name": "redes-neuronales-artificiales", | ||
| 265 | "state": "active", | 285 | "state": "active", | ||
| 266 | "vocabulary_id": null | 286 | "vocabulary_id": null | ||
| 267 | }, | 287 | }, | ||
| 268 | { | 288 | { | ||
| n | 269 | "display_name": "servicio-meteorolgico-nacional", | n | 289 | "display_name": "servicio-meteorologico-nacional", |
| 270 | "id": "3e4bb20a-2bab-41b4-b6aa-98d436370868", | 290 | "id": "f282d8bb-9473-4642-936d-e5ae23fec2d6", | ||
| 271 | "name": "servicio-meteorolgico-nacional", | 291 | "name": "servicio-meteorologico-nacional", | ||
| 272 | "state": "active", | 292 | "state": "active", | ||
| 273 | "vocabulary_id": null | 293 | "vocabulary_id": null | ||
| 274 | }, | 294 | }, | ||
| 275 | { | 295 | { | ||
| 276 | "display_name": "svaldez", | 296 | "display_name": "svaldez", | ||
| 277 | "id": "f42a8210-1cef-4f03-98a0-a6d3d0d4f848", | 297 | "id": "f42a8210-1cef-4f03-98a0-a6d3d0d4f848", | ||
| 278 | "name": "svaldez", | 298 | "name": "svaldez", | ||
| 279 | "state": "active", | 299 | "state": "active", | ||
| 280 | "vocabulary_id": null | 300 | "vocabulary_id": null | ||
| 281 | }, | 301 | }, | ||
| 282 | { | 302 | { | ||
| 283 | "display_name": "temperatura", | 303 | "display_name": "temperatura", | ||
| 284 | "id": "d8323c5c-8121-40ee-99c5-edecac595bdf", | 304 | "id": "d8323c5c-8121-40ee-99c5-edecac595bdf", | ||
| 285 | "name": "temperatura", | 305 | "name": "temperatura", | ||
| 286 | "state": "active", | 306 | "state": "active", | ||
| 287 | "vocabulary_id": null | 307 | "vocabulary_id": null | ||
| 288 | }, | 308 | }, | ||
| 289 | { | 309 | { | ||
| t | 290 | "display_name": "variables-meteorolgicas", | t | 310 | "display_name": "variables-meteorologicas", |
| 291 | "id": "1b20358f-aee2-4593-b34b-b89f262fdc38", | 311 | "id": "773b8668-0bc2-4ecf-a7d9-2b62104d3e76", | ||
| 292 | "name": "variables-meteorolgicas", | 312 | "name": "variables-meteorologicas", | ||
| 293 | "state": "active", | 313 | "state": "active", | ||
| 294 | "vocabulary_id": null | 314 | "vocabulary_id": null | ||
| 295 | }, | 315 | }, | ||
| 296 | { | 316 | { | ||
| 297 | "display_name": "zacatecas", | 317 | "display_name": "zacatecas", | ||
| 298 | "id": "035b6dd1-2780-467c-ba09-8d3a116ea222", | 318 | "id": "035b6dd1-2780-467c-ba09-8d3a116ea222", | ||
| 299 | "name": "zacatecas", | 319 | "name": "zacatecas", | ||
| 300 | "state": "active", | 320 | "state": "active", | ||
| 301 | "vocabulary_id": null | 321 | "vocabulary_id": null | ||
| 302 | } | 322 | } | ||
| 303 | ], | 323 | ], | ||
| 304 | "title": "Redes Neuronales para Predecir Datos Climatol\u00f3gicos", | 324 | "title": "Redes Neuronales para Predecir Datos Climatol\u00f3gicos", | ||
| 305 | "type": "dataset", | 325 | "type": "dataset", | ||
| 306 | "url": | 326 | "url": | ||
| 307 | ervatoriogeo.mx/redes-neuronales-para-predecir-datos-climatologicos/", | 327 | ervatoriogeo.mx/redes-neuronales-para-predecir-datos-climatologicos/", | ||
| 308 | "version": null | 328 | "version": null | ||
| 309 | } | 329 | } |