http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-108985326-A
Outgoing Links
| Predicate | Object |
|---|---|
| assignee | http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_ac31afbea1cbbb03498644721ffb4a62 |
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06Q50-06 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-24147 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-23 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06Q50-06 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-62 |
| filingDate | 2018-06-05^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor | http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_7cbb9f18599f2aa85fb153e7e3fa9e53 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_ab0bd05bccd4d08866fad1d4d9d2b9fe http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_ca76bef9bb36878024a717fac51c4b09 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_9e84af68501f050c54accfeed3c69cea |
| publicationDate | 2018-12-11^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-108985326-A |
| titleOfInvention | A Clustering-Based Method for Power System Demand Response User Labeling |
| abstract | The invention discloses a method for marking power system demand response users based on clustering, including: 1) collating demand response data of power users, distinguishing marked and unmarked power users, and extracting attribute data of all power users; 2) Use the nearest neighbor method to determine the boundary sample set in the marked power user set; 3) For the pairwise power users in the same category in the boundary sample set, based on the density weighting method, generate an example sample set of this category; 4) For the example sample set For each power user, use the nearest neighbor method to mark its adjacent unmarked power users; 5) Repeat the iterative process above until all unmarked power users have marked the demand response category. The method of the invention makes full use of the data characteristics of power users themselves, applies clustering ideas, and combines the distribution of power users in demand response categories, and completes the demand response category prediction of a large number of power users on the basis of a small number of labels. |
| priorityDate | 2018-06-05^^<http://www.w3.org/2001/XMLSchema#date> |
| type | http://data.epo.org/linked-data/def/patent/Publication |
Incoming Links
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