http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-114330549-A
Outgoing Links
| Predicate | Object |
|---|---|
| assignee | http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_6fec0bef233499f3d091ecb58997ae7e |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-04 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-62 |
| filingDate | 2021-12-28-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor | http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_79b77b9f32d799f52af3e85f179603b5 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_7bebc9069f5ebaeb9c9beec4f4748aa9 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_bbe9fca7320355d5f85de05be528f831 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_de8fed1ccff12617060df96bab58a038 |
| publicationDate | 2022-04-12-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-114330549-A |
| titleOfInvention | Chemical process fault diagnosis method based on depth map network |
| abstract | The invention discloses a chemical process fault diagnosis method based on a depth map network, which comprises the following steps: (1) acquiring and integrating data; (2) selecting and sorting data; (3) establishing a causal directed graph; (4) modeling training; (5) and (5) testing the model. The method adopts a chemical process fault diagnosis method based on a depth map network, improves the identification effect of the fault, simultaneously accurately positions the fault variable, and has universality and universality. |
| priorityDate | 2021-12-28-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type | http://data.epo.org/linked-data/def/patent/Publication |
Incoming Links
| Predicate | Subject |
|---|---|
| isDiscussedBy | http://rdf.ncbi.nlm.nih.gov/pubchem/substance/SID419479910 http://rdf.ncbi.nlm.nih.gov/pubchem/compound/CID5709 |
Total number of triples: 16.