| Defence Science Journal | |
| Highly Accurate Multi-layer Perceptron Neural Network for Air Data System | |
| H. S. Krishna1  | |
| [1] Aeronautical Development Agency, Bangalore | |
| 关键词: Back propagation; calibration; curve-fitting; error; inner product; logistic function; neuron; perceptron; pressure probe; training network; synaptic weights; | |
| DOI : | |
| 学科分类:社会科学、人文和艺术(综合) | |
| 来源: Defence Scientific Information & Documentation Centre | |
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【 摘 要 】
The error backpropagation multi-layer perceptron algorithm is revisited. This algorithm is used to train and validate two models of three-layer neural networks that can be used to calibrate a 5-hole pressure probe. This paper addresses Occam's Razor problem as it describes the adhoc training methodology applied to improve accuracy and sensitivity. The trained outputs from 5-4-3 feed-forward network architecture with jump connection are comparable to second decimal digit (~0.05) accuracy, hitherto unreported in literature. Defence Science Journal, 2009, 59(6), pp.670-674, DOI:http://dx.doi.org/10.14429/dsj.59.1574
【 授权许可】
Unknown
【 预 览 】
| Files | Size | Format | View |
|---|---|---|---|
| RO201912010140032ZK.pdf | 172KB |
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