http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-111445023-B
Outgoing Links
| Predicate | Object |
|---|---|
| classificationCPCAdditional | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-30188 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20221 |
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06V20-188 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T5-50 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-241 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-40 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-126 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-084 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-30 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-62 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T5-50 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-30 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-12 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-08 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-40 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06V10-764 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06V20-10 |
| filingDate | 2020-02-18-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| grantDate | 2022-04-19-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationDate | 2022-04-19-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-111445023-B |
| titleOfInvention | Genetic algorithm-optimized BP neural network GF-2 image forest classification method |
| abstract | A genetic algorithm-optimized BP neural network GF-2 image forest classification method, comprising the following steps: 1) dividing the surface vegetation in the classification area into three levels; 2) preprocessing the remote sensing images obtained in the classification area; 3) carrying out Add eigenvalues to the preprocessed remote sensing image spectrum to enhance the feature difference; 4) Establish the topology of the BP neural network; 5) Optimize the weights and thresholds by genetic algorithm; 6) Input the eigenvalues in the remote sensing image In the BP neural network algorithm, the classification of ground objects is completed. The genetic algorithm-optimized BP neural network GF-2 image forest classification method of the present invention overcomes the shortcomings of the genetic algorithm optimization that the stability of the BP neural network is not high, the final weights and thresholds are easy to fall into local optimum, and the classification effect cannot reach the best. The BP neural network GF-2 image forest classification method can further improve the classification accuracy. |
| priorityDate | 2020-02-18-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type | http://data.epo.org/linked-data/def/patent/Publication |
Incoming Links
Total number of triples: 41.