http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CA-2579011-A1
Outgoing Links
| Predicate | Object |
|---|---|
| assignee | http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_d622a0608e3aeef107d6d1c53e172695 |
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01V99-00 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G01V9-00 |
| filingDate | 2005-05-31-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor | http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_4bae9fb200fe93a88d301b51ce075590 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_957ab8469585323252e6205a61852c13 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_3813f88366f13c54940bc115f190f626 |
| publicationDate | 2006-02-16-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CA-2579011-A1 |
| titleOfInvention | Predicting sand-grain composition and sand texture |
| abstract | A method and apparatus for predicting sand-grain composition and sand texture are disclosed. A first set of system variables associated with sand-grain composition and sand texture is selected (605). A second set of system variables directly or indirectly causally related to the first set of variables is also selected (610). Data for each variable in the second set is estimated or obtained (615). A network with nodes including both sets of variables is formed (625). The network has a directional links connecting interdependent nodes. The directional links honor known causality relationships. A Bayesian network algorithm is used (630) with the data to solve the network for the first set of variables and their associated uncertainties. |
| priorityDate | 2004-07-07-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type | http://data.epo.org/linked-data/def/patent/Publication |
Incoming Links
Total number of triples: 17.