http://rdf.ncbi.nlm.nih.gov/pubchem/patent/KR-100969174-B1
Outgoing Links
| Predicate | Object |
|---|---|
| classificationCPCAdditional | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/B01D2257-302 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/Y10T436-12 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/B01D2257-404 |
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/B01D53-00 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G05B13-048 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06Q50-265 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G05B13-027 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06Q50-00 |
| filingDate | 2005-08-03-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| grantDate | 2010-07-14-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationDate | 2010-07-14-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | KR-100969174-B1 |
| titleOfInvention | Model predictive control of air pollution control processes |
| abstract | The controller 610 for directing the operation of the air pollution control system 620 to execute a process for controlling the release of contaminants has a number of process parameters (MPP) 625. One or more MPPs 625 are controllable process parameters (CTPP) 615, and one of the MPPs 625 is a large amount of contaminants (AOP) 640 emitted by the system 620. The defined AOP 640 value AOPV represents the target or limit for the actual value AV of the emitted 640. The controller 610 includes one of a neural network process model or a non-neural network process model that represents the relationship between each CTPP 615 and the released 640. The control processor 630 predicts how a change to the current value of each CTPP 615 affects the future AV of the emitted AOP 640 based on the model and based on the predicted impact of the change and AOPV. Select one of the changes in one CTPP 615 and have logic to direct control of one CTPP 615 according to the selected change to the CTPP 615.n n n n Air pollution, neural network, flue gas, gypsum, limestone, slurry |
| priorityDate | 2004-08-27-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type | http://data.epo.org/linked-data/def/patent/Publication |
Incoming Links
Total number of triples: 34.