OTEC-1 Power System Test Program: test plan for first deployment

Three methods of evaluating beef sires for weaning weight with data obtained from an organized young sire progeny testing program were compared. Information from Agriculture Canada’s National Beef Sire Monitoring Program was utilized along with computational procedures based on best linear unbiased prediction. The methods were applied to data from the Canadian Simmental Association as an illustration of the methods. A model which incorporates the proofs of the reference sires into the comparisons with test bulls was considered more appropriate than the other two models compared. The results also showed that even in an organized progeny test program, test bulls are not truly mated to cows of equal merit or across equal herd environments.

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Artificial Neural Networks as Applied to Aircraft Flight Test Planning / Wykorzystanie Sztucznych Sieci Neuronowych W Planowaniu Badań W Locie

Journal of Konbin ◽

10.2478/jok-2013-0014 ◽

2012 ◽

Vol 21 (1) ◽

pp. 149-162

Author(s):

Mirosław Zieja ◽

Joanna Wójcik

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Flight Test ◽

Test Plan ◽

Military Aircraft ◽

Test Program ◽

Aircraft Flight ◽

Artificial Neural ◽

Artificial Neural Network Ann ◽

The Military

Abstract Any flight test programme is essentially based on a flight test plan, i.e. a document agreed upon and accepted by all the parties interested in the tests, and authorised by the superior body/authorities responsible for the execution of the tests. The flight test plan determines the number of flights and flight hours indispensable to verify whether a given aircraft satisfies specified requirements. Many and various external factors may have significant and adverse effect on the execution of the flight test program according to the earlier agreed schedule. The study also covers the structure of a model of a management system for aircraft prototype testing, and the structure of artificial neural network (ANN) developed on the basis of experimentally gained data from the military aircraft testing. A mathematical model based on the artificial neural network and its potential for the managing of aircraft prototypes testing has been formulated as well.

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