http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-113947226-A
Outgoing Links
| Predicate | Object |
|---|---|
| assignee | http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_162dcd2fe0e67c8bc3e063a7e4c09e31 |
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06Q10-04 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06Q10-20 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06Q10-06315 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-214 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-23 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-22 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-2411 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06Q10-06 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06Q10-04 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06Q10-00 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-62 |
| filingDate | 2021-11-03-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor | http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_a5486349396b5df266e15042e4677d14 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_c88b13976dcc339ba37ae1efcd8d223f http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_82e1471d7b60cb21f43a90356c5a40a3 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_d281c6c0143ed6c6eb9fd8dddfc7b171 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_dbdcd607311f3b9f304d30dbe400f0a2 |
| publicationDate | 2022-01-18-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-113947226-A |
| titleOfInvention | A method for forecasting the demand for equipment maintenance equipment |
| abstract | The invention proposes a method for predicting the demand of equipment maintenance equipment. The demand data of equipment maintenance equipment in the past years are obtained, and after preprocessing, it is used as training set data; the training set data is classified by a clustering method, and the classification result after the classification is input into the classifier. , judge the categories corresponding to different classification types; build a training vector set according to the data categories, and use the support vector regression machine to predict the demand data of equipment maintenance equipment in the next few years. The invention considers the equipment maintenance equipment consumption data of different time starting points and the same time length as the data points of the model training set, classifies the training data through the AP clustering iterative algorithm, identifies the interference factors in the training data set, and establishes label training at the same time. Set, use SVM to identify test data points, and improve the reliability of SVR prediction results. Through the present invention, a more reliable equipment demand prediction result can be obtained, and at the same time, the interference of noise data on the result can be reduced. |
| priorityDate | 2021-11-03-04:00^^<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/SID419493476 http://rdf.ncbi.nlm.nih.gov/pubchem/compound/CID4235 |
Total number of triples: 26.