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  • 1.
    Bohlin, Markus
    et al.
    RISE - Research Institutes of Sweden (2017-2019), ICT, SICS.
    Forsgren, Malin
    RISE - Research Institutes of Sweden (2017-2019), ICT, SICS.
    Holst, Anders
    RISE., Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Levin, Björn
    RISE - Research Institutes of Sweden (2017-2019), ICT, SICS.
    Aronsson, Martin
    RISE., Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Steinert, Rebecca
    RISE., Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Reducing vehicle maintenance using condition monitoring and dynamic planning2008Inngår i: Proceedings of the 4th IET International Conference on Railway Condition Monitoring (RCM'08), 2008, 1Konferansepaper (Fagfellevurdert)
  • 2.
    Gillblad, Daniel
    et al.
    RISE., Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Holst, Anders
    RISE., Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Kreuger, Per
    RISE., Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Levin, Björn
    RISE - Research Institutes of Sweden (2017-2019), ICT, SICS.
    The gmdl Modeling and Analysis System2004Rapport (Annet vitenskapelig)
    Abstract [en]

    This report describes the gmdl modeling and analysis environment. gmdl was designed to provide powerful data analysis, modeling, and visualization with simple, clear semantics and easy to use, well defined syntactic conventions. It provides an extensive set of necessary for general data preparation, analysis, and modeling tasks.

    Fulltekst (pdf)
    FULLTEXT01
  • 3.
    Gillblad, Daniel
    et al.
    RISE., Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Holst, Anders
    RISE., Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Levin, Björn
    RISE - Research Institutes of Sweden (2017-2019), ICT, SICS.
    Emulating first principles process simulators with learning systems2005Inngår i: Artificial Neural Networks: Formal Models and Their Applications - ICANN 2005, Germany: Springer , 2005, 1, s. 377-382Kapittel i bok, del av antologi (Fagfellevurdert)
  • 4.
    Gillblad, Daniel
    et al.
    RISE., Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Holst, Anders
    RISE., Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Levin, Björn
    RISE - Research Institutes of Sweden (2017-2019), ICT, SICS.
    Aronsson, Martin
    RISE., Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    An English butler for complex industrial systems2003Inngår i: Proceedings of the 16th International Congress on Condition Monitoring and Diagnostic Engineering (COMADEM 2003), Växjö, Sweden: Växjö University Press , 2003, 1, , s. 9s. 405-413Konferansepaper (Fagfellevurdert)
  • 5.
    Gillblad, Daniel
    et al.
    RISE., Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Holst, Anders
    RISE., Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Levin, Björn
    RISE - Research Institutes of Sweden (2017-2019), ICT, SICS.
    Gudmundsson, Magnus
    RISE - Research Institutes of Sweden (2017-2019), ICT, SICS.
    Approximating process simulators with learning systems2005Rapport (Annet vitenskapelig)
    Abstract [en]

    We explore the possibility of replacing a first principles process simulator with a learning system. This is motivated in the presented test case setting by a need to speed up a simulator that is to be used in conjunction with an optimisation algorithm to find near optimal process parameters. Here we will discuss the potential problems and difficulties in this application, how to solve them and present the results from a paper mill test case.

    Fulltekst (pdf)
    FULLTEXT01
  • 6.
    Gillblad, Daniel
    et al.
    RISE., Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Kreuger, Per
    RISE., Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Levin, Björn
    RISE - Research Institutes of Sweden (2017-2019), ICT, SICS.
    Rudström, Åsa
    RISE., Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Preparation and analysis of multiple source industrial process data2005Rapport (Annet vitenskapelig)
    Abstract [en]

    Industrial process data is often stored in a wide variety of formats and in several different repositories. Efficient methodologies and tools for data preparation and merging are critical for efficient analysis of such data. Experience shows that data analysis projects involving industrial data often spend the major part of their effort on these tasks, leaving little room for model development and generating applications. This paper identifies and classifies the needs and individual steps in data preparation of industrial data. A methodology for data preparation specifically suited for the domain is proposed and a practically useful set of primitive operations to support the methodology is defined. Finally, a proof of concept data preparation system implementing the proposed operations and a scripting facility to support the iterations in the methodology is presented along with a discussion of necessary and desirable properties of such a tool.

    Fulltekst (pdf)
    FULLTEXT01
  • 7.
    Gillblad, Daniel
    et al.
    RISE., Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Kreuger, Per
    RISE., Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Rudström, Åsa
    RISE., Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Levin, Björn
    RISE - Research Institutes of Sweden (2017-2019), ICT, SICS.
    Data Preparation in Complex Industrial Systems2005Inngår i: Condition Monitoring and Diagnostic Engineering Management (COMADEM 2005), Cranfield, UK: Cranfield University Press , 2005, 5, s. 543-551Konferansepaper (Fagfellevurdert)
  • 8.
    Kanerva, Pentti
    et al.
    RISE., Swedish ICT, SICS.
    Sjödin, Gunnar
    RISE., Swedish ICT, SICS.
    Kristoferson, Jan
    RISE., Swedish ICT, SICS.
    Karlsson, R.
    Levin, Björn
    RISE - Research Institutes of Sweden (2017-2019), ICT, SICS.
    Holst, Anders
    RISE., Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Karlgren, Jussi
    RISE., Swedish ICT, SICS.
    Sahlgren, Magnus
    RISE - Research Institutes of Sweden (2017-2019), ICT, SICS.
    Computing with large random patterns2001Inngår i: Foundations of Real-World Intelligence, Stanford, California: CSLI Publications , 2001, 1, s. 251-311Kapittel i bok, del av antologi (Fagfellevurdert)
    Abstract [en]

    We describe a style of computing that differs from traditional numeric and symbolic computing and is suited for modeling neural networks. We focus on one aspect of ``neurocomputing,'' namely, computing with large random patterns, or high-dimensional random vectors, and ask what kind of computing they perform and whether they can help us understand how the brain processes information and how the mind works. Rapidly developing hardware technology will soon be able to produce the massive circuits that this style of computing requires. This chapter develops a theory on which the computing could be based.

  • 9.
    Levin, Björn
    et al.
    RISE - Research Institutes of Sweden (2017-2019), ICT, SICS.
    Holst, Anders
    RISE., Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Bohlin, Markus
    RISE - Research Institutes of Sweden (2017-2019), ICT, SICS.
    Steinert, Rebecca
    RISE., Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Aronsson, Martin
    RISE., Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Dynamic maintenance2008Inngår i: Proceedings of the 21st International Congress and Exhibition On Condition Monitoring and Diagnostic Engineering Management (COMADEM'08), 2008, 1Konferansepaper (Fagfellevurdert)
  • 10.
    Levin, Björn
    et al.
    RISE - Research Institutes of Sweden (2017-2019), ICT, SICS.
    Holst, Anders
    RISE., Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Lansner, Anders
    RISE - Research Institutes of Sweden (2017-2019), ICT, SICS.
    Haraszti, Zolt
    Simulation support and ATM performance prediction1998Inngår i: ICANN 98 Proceedings: International Conference on Artificial Neural Networks, 2-4 Sep 1998, Skövde, Sweden, 1998, 1Konferansepaper (Fagfellevurdert)
  • 11.
    Sjödin, Gunnar
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Kanerva, Pentti
    RISE - Research Institutes of Sweden, ICT, SICS.
    Levin, Björn
    RISE - Research Institutes of Sweden, ICT, SICS.
    Kristoferson, Jan
    RISE - Research Institutes of Sweden, ICT, SICS.
    Holistic higher-level structure-forming algorithms1998Inngår i: Proceedings of the Real World Computing Symposium (RWC'98), 1998, Tokyo, Japan, 1998, 1Konferansepaper (Fagfellevurdert)
1 - 11 of 11
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  • en-GB
  • en-US
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  • text
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