Probabilistic and other neural nets in multi-hole probe calibration and flow angularity pattern recognition

被引：6

作者：

Baskaran, S ^{[1
]}

Ramachandran, N

Noever, D

机构：

[1] Raytheon Co, STX MSFC NASA E576, Huntsville, AL 35812 USA

[2] Univ Vienna, Inst Theoret Chem, Vienna, Austria

[3] NASA, Univ Space Res Assoc, Huntsville, AL 35812 USA

[4] NASA, George C Marshall Space Flight Ctr, Huntsville, AL 35812 USA

来源：

PATTERN ANALYSIS AND APPLICATIONS | 1999年 / 2卷 / 01期

关键词：

calibration wind tunnel; fluid dynamics; multi-hole probes; numerical simulation; probabilistic neural nets;

D O I：

10.1007/s100440050018

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The use of probabilistic (PNN) and multilayer feedforward (MLFNN) neural networks is investigated for the calibration of multi-hole pressure probes and the prediction of associated flow angularity patterns in test flow fields. Both types of network are studied in detail for their calibration and prediction characteristics. The current formalism can be applied to any multi hole probe, however the test results for the most commonly used five-hole Cone and Prism probe types alone are reported in this paper.

引用

页码：92 / 98

页数：7

共 11 条

[1]

JANES CE, 1978, 487 D TAYL MOD BAS

[2]

Krause L.N., 1969, NASA TMX 52576

[3]

NARENDRA KS, 1990, IEEE T NEURAL NETWOR, P14

[4] Artificial neural network prediction of tetragonal lysozyme face growth rates [J].

Noever, D ;

Pusey, ML ;

Forsythe, EL ;

Baskaran, S .

JOURNAL OF CRYSTAL GROWTH, 1996, 167 (1-2) :221-236

[5]

NOEVER D, 1997, J MATER RES, V12, P1

[6]

PIEN PC, 1958, 1229 D TAYL MOD BAS

[7]

RAMACHANDRAN N, 1992, MSFCED35 NASA

[8]

RAMACHANDRAN R, 1994, USRAED36 NASA MSFC

[9] A GENERAL REGRESSION NEURAL NETWORK [J].

SPECHT, DF .

IEEE TRANSACTIONS ON NEURAL NETWORKS, 1991, 2 (06) :568-576

[10]

TREASTER AL, 1979, ISA T, V18, P23

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