Applying of Neural Networks for Testing of Tracers with using of Empirical Data

Author:

Ampuła Dariusz1

Affiliation:

1. Military Institute of Armament Technology , Wyszyńskiego 7 Str., 05-220 Zielonka , Poland

Abstract

Abstract An attempt of designing artificial neural networks for empirical laboratory test results tracers No. 5, No. 7 and No. 8 was introduced in the article. These tracers are applied in cartridges with calibres from 37 mm to 122 mm which are still used and stored both in the marine climate and land. The results of laboratory tests of tracers in the field of over 40 years of tests have been analysed. They have been properly prepared in accordance with the requirements that are necessary to design of neural networks. Only the evaluation module of these tracers was evaluated, because this element of tests, fulfilled the necessary assumptions needed to build artificial neural networks. Several hundred artificial neural networks have been built for each type of analysed tracers. After an in-depth analysis of received results, it was chosen one the best neural network, the main parameters of which were described and discussed in the article. Received results of working built of neural networks were compared with previously functioning manual evaluation module of these tracers. On the basis conducted analyses, proposed the modification of functioning test methodology by replacing the previous manual evaluation modules through elaborated automatic models of artificial neural networks. Artificial neural networks have a very important feature, namely they are used in the prediction of specific output data. This feature successfully used in diagnostic tests of other elements of ammunition.

Publisher

Walter de Gruyter GmbH

Reference10 articles.

1. [1] Amunicja wojsk lądowych, collective work, Publ. Ministerstwo Obrony Narodowej, Warszawa 1985 [The ammunition of ground forces — available in Polish].

2. [2] Domaradzki R., Zastosowanie sieci neuronowych do generowania strategii decyzyjnych (inwestycyjnych), PhD thesis, Publ. Akademia Górniczo-Hutnicza, Kraków 2007 [Application of neural networks to generating of strategies decision’s (investment) — available in Polish].

3. [3] Helt P., Parol M., Piotrowski P., Metody sztucznej inteligencji, Publ. Oficyna Wydawnicza Politechniki Warszawskiej, Warszawa 2012 [Methods of the artificial intelligence — available in Polish].

4. [4] Karty z badań laboratoryjnych smugaczy nr 5, nr 7 i nr 8, Archives WITU, 1969–2010 [Cards from laboratory tests of tracers No. 5, No. 7 and No. 8 — available in Polish].

5. [5] Metodyka badań diagnostycznych amunicji, collective work, Archives WITU, Index N-5001b, 1985 [The methodology of diagnostic tests of ammunition — available in Polish].

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