Name
Abstract | ||
|---|---|---|
In this paper, a novel modeling method of difference pressure mass flow measurement nonlinear correction based on Support Vector Machine is introduced. Support Vector Machine is a novel machine learning method, which identify the correction model definitely just according to the samples. Flow measurement nonlinear correction is a small sample problem. The result of the simulation for orifice flowmeter error correction based on SVM shows that this method can get a better effect. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-87442-3_110 | ICIC (1) |
Keywords | Field | DocType |
small sample problem,novel machine,support vector machine,flowmeter nonlinear calibration,orifice flowmeter error correction,novel modeling method,correction model,difference pressure mass flow,measurement nonlinear correction,flow measurement nonlinear correction,multi-parameter differential pressure,better effect,data fusion,flow measurement,error correction,machine learning | Nonlinear system,Pattern recognition,Computer science,Flow measurement,Support vector machine,Body orifice,Error detection and correction,Sensor fusion,Artificial intelligence,Mass flow,Calibration,Machine learning | Conference |
Volume | ISSN | Citations |
5226 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 4 | 3 |