Mathematical model of chemical process prediction for industrial safety risk assessment

Autor: Artamonov, Alexey A., Bogdanova, Leila M., Nagibin, Sergey Ya., Loskutov, Dmitry I., Chemakin, Alexander S.

Publikováno v: In Procedia Computer Science 2021 190:107-114

Analysis of Neural Networks for Predicting Time Series When Assessing Industrial Safety Risks

Autor: Ya. Nagibin, Sergey, I. Loskutov, Dmitry

Publikováno v: TEM Journal. 9(2):477-483

Externí odkaz: https://www.ceeol.com/search/article-detail?id=869811

Analysis of Neural Networks for Predicting Time Series When Assessing Industrial Safety Risks.

Autor: Nagibin, Sergey Ya.¹, Loskutov, Dmitry I.¹ nagibin.s.ya@mail.ru

Publikováno v: TEM Journal. 2020, Vol. 9 Issue 2, p477-483. 7p.

Key comparison CCQM-K73 amount content of H+ in hydrochloric acid (0.1 mol·kg-1)

Autor: Pratt, Kenneth W., Ortiz-Aparicio, Jose Luis, Matehuala-Sanchez, Francisco Javier, Pawlina, Monika, Kozłowski, Władysław, Borges, Paulo P., da Silva Junior, Wiler B., Borinsky, Mónica B., Hernandez, Ana, Puelles, Mabel, Hatamleh, Nadia, Acosta, Osvaldo, Nunes, João, Guiomar Lito, M. J., Camões, M. Filomena, Filipe, Eduarda, Hwang, Euijin, Lim, Youngran, Bing, Wu, Qian, Wang, Chao, Wei, Hioki, Akiharu, Asakai, Toshiaki, Máriássy, Michal, Hanková, Zuzana, Nagibin, Sergey, Manska, Olexandra, Gavrilkin, Vladimir, Kutovoy, Viatcheslav

Publikováno v: Metrología, 50
Repositorio Institucional del Instituto Nacional de Tecnología Industrial (INTI)
Instituto Nacional de Tecnología Industrial
instacron:INTI

This key comparison (KC), CCQM-K73, was performed to demonstrate the capability of the participating National Metrology Institutes (NMIs) to measure the amount content of H+ , νH + , in an HCl solution with a nominal νH + of 0.1 mol·kg-1 . A paral

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______3056::4d8e8c309aedec0051309a2d5ab01563
https://app.inti.gob.ar/greenstone3/sites/localsite/collect/nuevadc/index/assoc/Borinsky.dir/doc.pdf