Object's details: Performance of artificial neural networks in an inverse problem of laser beam diagnostics

Provider:Czasopisma PAN

Description

Title:
Performance of artificial neural networks in an inverse problem of laser beam diagnostics
Creator:
Pietrak, Karol;
Muszyński, Radosław;
Marek, Adam;
Łapka, Piotr
Contributor:
Pietrak, Karol : Faculty of Power and Aeronautical Engineering, Warsaw University of Technology, ul. Nowowiejska 24, 00-665 Warsaw, Poland;
Muszyński, Radosław : Faculty of Power and Aeronautical Engineering, Warsaw University of Technology, ul. Nowowiejska 24, 00-665 Warsaw, Poland;
Marek, Adam : Faculty of Power and Aeronautical Engineering, Warsaw University of Technology, ul. Nowowiejska 24, 00-665 Warsaw, Poland;
Łapka, Piotr : Faculty of Power and Aeronautical Engineering, Warsaw University of Technology, ul. Nowowiejska 24, 00-665 Warsaw, Poland
Description:
The Bulletin of the Polish Academy of Sciences Technical Sciences is published bimonthly by the Division IV Engineering Sciences of the Polish Academy of Sciences, since the beginning of the existence of the PAS in 1952. The journal is peer‐reviewed and is published both in printed and electronic form. It is established for the publication of original high quality papers from multidisciplinary Engineering sciences with the following topics preferred: Artificial and Computational Intelligence, Biomedical Engineering and Biotechnology, Civil Engineering, Control, Informatics and Robotics, Electronics, Telecommunication and Optoelectronics, Mechanical and Aeronautical Engineering, Thermodynamics, Material Science and Nanotechnology, Power Systems and Power Electronics. Submit your article Journal Metrics: JCR Impact Factor 2022: 1.2 5 Year Impact Factor 2020: 1.490 CiteScore 2022: 2.8 SCImago Journal Rank (SJR) 2022: 0.285 Source Normalized Impact per Paper (SNIP) 2022: 0.543 Ministry of Education and Science: 100 points Abbreviated title: Bull. Pol. Acad. Sci. Tech. Sci.;
Editorial Board 2023-2025 Editor-in-Chief: A. Rogalski, Military University of Technology Honorary (Past) Editor-in Chief: T. Kaczorek, Warsaw University of Technology M.P. Kaźmierkowski, Warsaw University of Technology Deputy Editor-in-Chief: B. Błachowski, Institute of Fundamental Technological Research PAN M. Mrozowski, Gdansk University of Technology Board of Topical Co-editors: Artificial and Computational Intelligence S. Osowski, B. Sawicki and T. Leś, Warsaw University of Technology Biomedical Engineering and Biotechnology D. Pijanowska, Institute of Biocybernetics and Biomedical Engineering PAN Civil Engineering L. Czarnecki, Building Research Institute, ITB, Warsaw Ł. Sadowski, Wroclaw University of Science and Technology Control, Robotics and Informatics J. Klamka and A. Babiarz, Silesian Technical University J. Stefanowski, Poznan University of Technology Electronics, Telecommunication and Optoelectronics M. Mrozowski and A. Lamęcki, Gdansk University of Technology Mechanical and Aeronautical Engineering, Thermodynamics B. Błachowski and P. Korczyk, Institute of Fundamental Technological Research PAN Materials Science and Nanotechnology B. Major and P. Czaja, Institute of Metallurgy and Materials Science PAN Power Systems and Power Electronics J. Rąbkowski and M. Jasiński, Warsaw University of Technology International Editorial Advisory Board R. Asthana, University of Wisconsin-Stout, Menomonie, USA Xu Binshi, China Association of Plant Engineering, Beijing, P.R. China F. Blaabjerg, Aalborg University, Denmark C. Cecati, University of L’Aquila, Italy A. Cichocki, RIKEN Institute, Tokyo, Japan M. David, National Polytechnique de Toulouse, France R. Ebner, Materials Centre Leoben, Leoben, Austria E. Fornasini, University of Padova, Padova, Italy L.G. Franquelo, University of Sevilla, Spain M. Gad-el-Hak, Virginia Commonwealth University, Richmond, USA M. Giersig, Free University of Berlin, Germany D. van Gemert, Catholic University Leuven, KU Leuven, Belgium L. Keviczky, Hungarian Academy of Sciences, Budapest, Hungary V. Kučera, Czech Technical University in Prague, Prague, Czech Republic R. Kennel, Technical University Munich, Germany T.A. Kowalewski, Institute of Fundamental Technological Research PAN E. Levi, Liverpool John Moore University, UK G. Maier, Technical University of Milan, Milan, Italy K.F. Man, City University of Hong Kong, R. Maniewski, Institute of Biocybernetics and Biomedical Engineering PAN H.A. Mang, Austrian Academy of Sciences, Vienna, Austria H. Mihashi, Tohoku University, Aoba-ku, Sendai, Japan S. Mindess, University of British Columbia, Vancouver, Canada D.A. Mlynski, University of Karlsruhe, Karlsruhe, Germany A.S. Nowak, University of Michigan, Ann Arbor, USA K. Ohnishi, Keio University, Yokohama, Japan A. Öberg, Linköping University, Linköping, Sweden W. Pedrycz, University of Alberta, Canada M. Razeghi, Northwestern University, Evanston, USA J. Rodriguez, University of Andres Bello, Santiago, Chile J.V. Sloten, Catholic University Leuven, Leuven, Belgium B.M. Wilamowski, University of Auburn, Alabama, USA A.L. Yarin, University of Illinois at Chicago, USA Du Xiangwan, Chinese Academy of Engineering, China J. Żurada, Department of Computer Engineering, University of Louisville, USA
Object availability:
free access
Rights:
Bulletin of the Polish Academy of Sciences Technical Sciences jest czasopismem wydawanym w wolnym dostępie na licencji CC BY 4.0. </span></p><p style="background: white;"><span style="font-size: 10pt;"> Bulletin of the Polish Academy of Sciences Technical Sciences is an open access journal with all content available with no charge in full text version. The journal content is available under the licencse CC BY 4.0.
Date:
2022.02.25
Type:
Article
Coverage:
e140100
Subject:
inverse problems;
pattern recognition;
laser beams
Identifier:
ISSN 2300-1917
Data provider:
Czasopisma PAN

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Federacja Bibliotek Cyfrowych

Object's details: Performance of artificial neural networks in an inverse problem of laser beam diagnostics

Description

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