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Search: subject:"the impact of the decisions on the modeled process is simulated"
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Industrial Engineering
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Models and algorithms for effective decision-making in a data-driven environment are discussed. To enhance the quality of the extracted knowledge and decision-making
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Sustainability
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a subset of rules is selected from the extracted knowledge to meet the established decision-making criteria. The parameter values represented by the conditions of this set of rules are called a decision signature. A model and algorithms for the selection of the desired parameters (decision signatures) will be developed. The parameters of this model are updated using a framework provided by the learning classifier systems
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and the parameters optimizing process performance are recommended. The applications discussed in this paper differ from most data mining tasks
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in a typical data mining application the equipment fault is recognized based on the failure symptoms. In this paper
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the data sets are transformed
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the impact of the decisions on the modeled process is simulated
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the knowledge is extracted with multiple algorithms
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where the extracted knowledge is used to assign decision values to new objects that have not been included in the training data. For example
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Kusiak, Andrew
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Data mining and decision making
Kusiak, Andrew
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2002
algorithms,
the
impact
of
the
decisions
on
the
modeled
process
is
simulated
, and the parameters optimizing process performance …
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