Improving Goal-Driven Simulation Performance Using Fuzzy Membership Correlation Analysis
作者： Emmanuel Ferreyra , Hani Hagras , Mathias Kern , Gilbert Owusu
DOI: 10.1109/CEEC.2018.8674239
关键词:
摘要: This paper proposes a method to improve achieving desired business-goals by finding the appropriate input configuration for Goal-Driven Simulation (GDS) approach based on an interval type-2 Fuzzy Logic System that allows evaluating solutions before implementing them in real-world scenarios. Therefore, we employ fuzzy membership correlation analysis improving goal-driven simulation performance field scheduling processes within service industry. The proposed methodology reported improved results comparison with its counterpart type-1 FLS and without mentioned analysis, respectively. work can assist providers focusing parameters are highly related achievement of business targets. Which, turn might contribute companies’ market presence, profitability customer satisfaction delivering right at time, while providing sensible accuracy concise interpretability.
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