| Predicate |
Object |
| assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_06492acdf821d7f492309c0ef33cda1b |
| classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-2411
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-295
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-2135
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-006 |
| classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-62
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-00 |
| filingDate |
2021-09-02-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_1c7bc9e0fba890a505e6168a8611227c
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_a1d60b004a3234155c9de9be7feda44e
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_86d6651ece5116845aceb3fa2c78ba6f
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_6966331eb2ed76e359e00b42c6426e29
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_9ff619e86305bd8013b0c8debcf5f144
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_f7cd76f2c4679cb4bfccdb488b060001
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_98c318493118afca65eb5898fbc7467d
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_efa4339df502371abc63b7097956cdc2
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_9d95a5927f983b5b806922af8a2d2a43
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_99e94150971851e8ebf5d5158f4afd85
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_f53e6c8606ace90d92202cefa4adfb0e
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_7e8ba50ea912991504466f434f32df5d
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_634dab1cf77424f7008a8271d6ab58cf
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_3e4623db8a0be1fff1701c300a64902d |
| publicationDate |
2021-11-30-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber |
CN-113723541-A |
| titleOfInvention |
A Slope Displacement Prediction Method Based on Hybrid Intelligent Algorithm |
| abstract |
The invention relates to a slope displacement prediction method based on a hybrid intelligent algorithm, comprising the following steps: collecting monitoring information of the slope, and establishing a database according to the monitoring information; eliminating redundant information in the database; reducing the dimension of data in the database; Make training samples and test samples from the data in the database; build a model, train the model through the training samples to obtain a first prediction model; modify the first prediction model through the test samples to obtain a second prediction model; pass the second prediction model The displacement of the target slope is predicted with the real-time monitoring information of the target slope to obtain the first predicted value; the first predicted value is corrected by the Markov method to obtain the final predicted value. The invention eliminates redundant information in the collected information, and reduces the dimension thereof, so that the prediction result is more accurate and the calculation amount is lower. The slope displacement is predicted by least squares support vector machine and particle swarm optimization algorithm. |
| isCitedBy |
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-116561563-B
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-116561563-A |
| priorityDate |
2021-09-02-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type |
http://data.epo.org/linked-data/def/patent/Publication |