http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-114037163-A
Outgoing Links
| Predicate | Object |
|---|---|
| assignee | http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_47d0c46a02d59ba47699c84801c25a1f |
| classificationCPCAdditional | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/Y02A20-152 |
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-084 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06Q10-04 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06Q50-26 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-23 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-006 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06Q50-26 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-08 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-62 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-00 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06Q10-04 |
| filingDate | 2021-11-10^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor | http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_fb0f9cee8f68dd7e5e1250dd3a34d0a0 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_927d95a1ea03aa29ed5f90e28045e2c3 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_8d110a1dd2ba9bfacf319f6b1e463cf8 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_6cf19aa9c2f4039d32eb67ef74e33762 |
| publicationDate | 2022-02-11^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-114037163-A |
| titleOfInvention | An early warning method of wastewater treatment effluent quality based on dynamic weight PSO optimization BP neural network |
| abstract | The invention discloses an early warning method for sewage treatment effluent quality based on dynamic weight PSO particle swarm algorithm optimization of BP neural network. The method is realized based on the following steps: 1) On the basis of analyzing the A2O sewage treatment process, through correlation analysis Determine six key indicators such as influent flow, influent total nitrogen, influent COD, dissolved oxygen concentration, redox potential ORP, and influent PH value as the input variables of the effluent total nitrogen and effluent COD prediction model, and predict the data. 2) Establish a sewage treatment effluent quality prediction model based on dynamic weight PSO optimized BP neural network, and verify the accuracy of the model; 3) Using the established model, input the data set of 6 key indicators, The total nitrogen in the effluent and the COD in the effluent are predicted, and the corresponding early warning is given by analyzing the prediction results. The invention has a reasonable design, not only solves the problems of complex and redundant structure and easy to fall into local extreme values when the traditional BP neural network predicts the effluent quality, but also improves the prediction accuracy of the effluent quality to a large extent. The quality of the effluent has been pre-warned, which can achieve the effect of predicting and responding in advance. |
| isCitedBy | http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-114202065-A http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-115240060-A |
| priorityDate | 2021-11-10^^<http://www.w3.org/2001/XMLSchema#date> |
| type | http://data.epo.org/linked-data/def/patent/Publication |
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