Wavelet morphometric neural network algorithm for analyzing nanomaterial porous texture
| العنوان: | Wavelet morphometric neural network algorithm for analyzing nanomaterial porous texture |
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| المؤلفون: | O. B. Butusov, V. G. Sevastianov, Valery Meshalkin, E. G. Vinokurov, A. B. Galaev, P. D. Sarkisov |
| المصدر: | Theoretical Foundations of Chemical Engineering. 46:329-337 |
| بيانات النشر: | Pleiades Publishing Ltd, 2012. |
| سنة النشر: | 2012 |
| مصطلحات موضوعية: | Artificial neural network, Computer science, business.industry, General Chemical Engineering, Binary number, Pattern recognition, General Chemistry, computer.software_genre, Texture (geology), Nanomaterials, Photo image, Wavelet, Cluster (physics), Data mining, Artificial intelligence, Porosity, business, computer |
| الوصف: | A wavelet morphometric neural network algorithm for analyzing the porous texture of a nanomaterial that differs from the use of the procedure for identifying the binary clusters for the morphometric analysis obtained as a result of the analysis of the neural network cluster of a micro photo image of a nanomaterial instead of the procedure for identifying binary objects on binary cross sections of the original micro photo image have been proposed. Using this algorithm, we calculated the quantitative morphometric estimations of the geometric parameters of the nanocluster texture of solid and porous components, which have been applied to predict the density distribution of pores inside of a nanomaterial. |
| تدمد: | 1608-3431 0040-5795 |
| DOI: | 10.1134/s004057951204015x |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::731f104a56a5a6e063bdbe33d8eba8ec https://doi.org/10.1134/s004057951204015x |
| Rights: | CLOSED |
| رقم الانضمام: | edsair.doi...........731f104a56a5a6e063bdbe33d8eba8ec |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 16083431 00405795 |
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| DOI: | 10.1134/s004057951204015x |