Opis

• Tytuł:
  A New Neural Networks Model for Calculating the Continuous Cooling Transformation Diagrams
• Twórca:
  Trzaska, J.
• Opis:
  Archives of Metallurgy and Materials is a quarterly of Polish Academy of Sciences and Institute of Metallurgy and Materials Science of the Polish Academy of Sciences, which publishes original scientific papers and reviews in the fields of metallurgy and materials science. Papers with focus on synthesis, processing and properties of metal materials, including thermodynamic and physical properties, phase relations, and their relation to microstructure of materials are of particular interest. IMPACT FACTOR 2022: 0.6 CiteScore 2022 - 1,20 SNIP 2022 - 0,300 SJR 2022 - 0,189 Score of the Ministry of Science and Higher Education = 70 Submit your article;
  EDITORIAL BOARD Editor-in-Chief: Paweł Zięba, Institute of Metallurgy and Materials Science PAS, Poland EDITORS Krzysztof Fitzner, AGH University of Science and Technology, Poland Bogusław Major, Institute of Metallurgy and Materials Science PAS, Poland Przemysław Fima, Institute of Metallurgy and Materials Science PAS, Poland Piotr Bała, AGH University of Science and Technology, Poland Maciej Szczerba, Institute of Metallurgy and Materials Science PAS, Poland Romana Ewa Śliwa, Rzeszow Univesity of Technology, Poland Wojciech Święszkowski, Warsaw University of Technology, Poland EDITORIAL ADVISORY BOARD Leszek Blacha, Silesian University of Technology, Poland Zbigniew Bojar, Military University of Technology, Poland Eduardo Cesari, University of the Balearic Islands, Spain Kyu Rhee Chang, Korea Atomic Energy Research Institute, Korea Volodymyr Chernenko, Basque Center For Materials, Spain Jan Dusza, Institute of Materials Research, SAS, Slovakia Władysław Gąsior, Institute of Metallurgy and Materials Science PAS, Poland Volodymyr Golub, Institute of Magnetism NASU, Ukraine Zbigniew Gronostajski, Wroclaw University of Technology, Poland Edward Guzik, AGH University of Science and Technology, Poland George Kaptay, Research Institute on Nanotechnology, Hungary Alexandre Kodentsov, Eindhoven University of Technology, Netherlands Rafał Kozubski, Jagiellonian University, Poland Aleš Kroupa, Institute of Physics of Materials AS CR, Czech Republic Piotr Kula, Lodz University of Technology, Poland Jan Kusiński, AGH University of Science and Technology, Poland Roman Kuziak, Institute of Ferrous Metallurgy, Poland Jüergen Lackner, Laser Center Leoben, Joanneum Research, Austria Kee Ahn Lee, Inha University, Korea Marcin Leonowicz, Warsaw University of Technology, Poland Małgorzata Lewandowska, Warsaw University of Technology, Poland Jerzy Lis, AGH University of Science and Technology, Poland Viktor Lvov, Kyiv National University, Ukraine Leszek B. Magalas, AGH University of Science and Technology, Poland Graeme E. Murch, University of Newcastle, Australia Marcin Nabiałek, Czestochowa University of Technology, Poland Alberto Passerone, Institute of Physical Chemistry of Materials, Italy Eugen Rabkin, Technion Israel Institute of Technology, Israel Amir Shirzadi, University of Cambridge, United Kingdom Jerzy Sobczak, Foundry Research Institute, Poland Boris B. Straumal, Russian Academy of Sciences, Russia Pekka Taskinen, Aalto University, Finland Stefan Zaefferer, Max-Planck-Institut, Germany Ehrenfried Zschech, Fraunhofer Institute for Non-Destructive Testing, Germany BOARD OF REVIEW Janusz Adamiec, Marek Blicharski, Marcin Brzeziński, Ryszard Dąbrowski, Stanisław Dymek, Robert Filipek, Franciszek Grosman, Halina Garbacz, Marcin Górny, Adam Grajcar, Marek Hetmańczyk, Jarosław Jakubski, Mieczysław Jurczyk, Agnieszka Kopia, Marian Kucharski, Beata Leszczyńska-Madej, Marcin Leonowicz, Łukasz Madej, Piotr Migas, Maciej Motyka, Jerzy Pacyna, Zbigniew Pędzich, Łukasz Rauch, Kinga Rodak, Maria Sozańska, Tomasz Tański, Krzysztof Wierzbanowski, Joanna Wojewoda-Budka, Waldemar Wołczyński, Piotr Żabiński;
  Archives of Metallurgy and Materials is covered by the following services: Arianta, Baidu Scholar, BazTech, Celdes, Chemical Abstracts Service (CAS) - CAplus, Clarivate Analytics (formerly Thomson Reuters) - Current Contents/Engineering, Computing, and Technology, Clarivate Analytics (formerly Thomson Reuters) - Journal Citation Reports/Science Edition, Clarivate Analytics (formerly Thomson Reuters) - Materials Science Citation Index, Clarivate Analytics (formerly Thomson Reuters) - Science Citation Index Expanded, CNKI Scholar (China National Knowledge Infrastructure), CNPIEC, DOAJ (Directory of Open Access Journals), EBSCO (relevant databases), EBSCO Discovery Service, Elsevier - SCOPUS, Genamics JournalSeek, Google Scholar, Index Copernicus, J-Gate, JournalTOCs, KESLI-NDSL (Korean National Discovery for Science Leaders), Microsoft Academic, Naviga (Softweco), Primo Central (ExLibris), ProQuest (relevant databases), ReadCube, ResearchGate, SCImago (SJR), Sherpa/RoMEO, Summon (Serials Solutions/ProQuest), TDNet, TEMA Technik und Management, Ulrich's Periodicals Directory/ulrichsweb, WanFang Data, WorldCat (OCLC)
• Dostępność obiektu:
  Dostęp otwarty
• Prawa:
  Articles are printed in an open access and distributed under the terms of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0, <a href="https://creativecommons.org/licenses/by-nc/4.0/"> https://creativecommons.org/licenses/by-nc/4.0/</a>.). This license allows authors to copy and redistribute the material in any medium or format, remix, transform, and build upon the material. Authors may not use the material for commercial purposes. However, this condition does not include dependent works (they may be covered by another license).
• Data:
  2018.12.12
• Typ:
  Artykuły / Articles
• Źródło:
  Archives of Metallurgy and Materials; 2018; vol. 63; No 4; 2009-2015
• Zakres:
  2009-2015
• Wydawca:
  Institute of Metallurgy and Materials Science of Polish Academy of Sciences;
  Committee of Materials Engineering and Metallurgy of Polish Academy of Sciences
• Temat i słowa kluczowe:
  CCT diagram;
  modelling;
  neural network;
  heat treatment;
  steel;
  Nauki Techniczne
• Identyfikator:
  ISSN 1733-3490
• Dostawca danych:
  Czasopisma PAN
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  sprawdź warunki licencji
• Rodzaj zawartości:
  obrazy