http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-113948203-A
Outgoing Links
| Predicate | Object |
|---|---|
| assignee | http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_d94573ab2c57e8b193f3a22accddf9fe |
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-045 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-08 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H50-20 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H50-70 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-08 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16H50-70 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-04 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16H50-20 |
| filingDate | 2021-10-21-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor | http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_385e2f80f831030cc929e96cc091aa27 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_04041a1f496f731be6c572924fcbf937 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_fd98957c370dfbe1ff5305860b2f3945 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_2545ccbd512c0b9b8f9ca98d0e083e03 |
| publicationDate | 2022-01-18-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-113948203-A |
| titleOfInvention | A fast prediction method based on convolutional neural network |
| abstract | The invention discloses a fast prediction method based on a convolutional neural network, and relates to the field of deep learning. The invention includes the following steps: acquiring gas, and using the gas sensor array to identify the gas; acquiring the response curve of the gas sensor array for gas identification; acquiring and extracting characteristic values from the response curve; preprocessing and normalizing the characteristic values to obtain the characteristic value data set; the feature data set is randomly divided into a training data set and a test data set; the training data set is input into the CNN neural network for training, and a prediction neural network model is obtained. The invention utilizes the convolutional neural network to process and analyze the characteristic data set generated by the gas passing through the acetone series gas sensor array, to predict the data, and then assist the doctor to diagnose the patient. |
| isCitedBy | http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-116189800-B http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-116189800-A |
| priorityDate | 2021-10-21-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type | http://data.epo.org/linked-data/def/patent/Publication |
Incoming Links
Total number of triples: 91.