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Computational intelligence framework for context-aware decision making

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Abstract

Learning of context-aware systems is necessary in building up knowledge on the characteristics of the environment to provide efficient decision making within multi-objective requirements. As the industrial systems becomes complex day-by-day, intelligent machine learning techniques need to be implemented at respective context-aware situations to facilitate recommendations using soft computing methods based on dynamic user specifications. In this paper, a framework is designed for a meta-database that is generated by contextual information of several peers with what-if conditions and rule-based approaches and thus by provide decision making utilizing several existing soft computing algorithms.

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  1. Division of Operation and Maintenance, Luleå University of Technology, Luleå, Sweden

    Adithya Thaduri & Uday Kumar

  2. Haugesund University College, Haugesund, Norway

    Ajit Kumar Verma

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  1. Adithya Thaduri
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  2. Uday Kumar
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  3. Ajit Kumar Verma
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Correspondence to Adithya Thaduri.

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Thaduri, A., Kumar, U. & Verma, A.K. Computational intelligence framework for context-aware decision making. Int J Syst Assur Eng Manag 8 (Suppl 4), 2146–2157 (2017). https://doi.org/10.1007/s13198-014-0320-8

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