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The processed data was then utilized to construct a case based reasoning (CBR) model for estimating the environmental load.
A common practice is to combine the predictions of several models into an overall outcome using consensus based reasoning.
The Case Based Reasoning (CBR) approach is used to manage both the user model and the device model.
This cognitive function of models has been widely acknowledged in the literature, and some even suggest that models give rise to a new style of reasoning, so-called 'model based reasoning' (Magnani and Nersessian 2002, Magnani, Nersessian and Thagard 1999).
"Modelling the Longevity of Dental Restorations by means of a CBR System" presents a case based reasoning (CBR) system to analyze dental restorations with different materials.
This model is based on the synergy between: TRIZ (Russian acronym for Theory of Inventive Problem Solving) and Case Based Reasoning (CBR).
To model the second framework, we developed a hybrid cognitive engine (CE) architecture by integrating an RNN based learning algorithm with genetic algorithm (GA) based reasoning.
Apart from a different statistical approach, several frameworks in human reasoning like case based reasoning [ 26], fuzzy reasoning [ 27], or fast and frugal heuristics [ 28] have been proposed to model the underlying cognitive processes in classification.
In this mechanism, a trust reasoning model based on fuzzy Petri net is presented to evaluate trust values of mobile nodes.
Run-time optimization strategies were recommended by the case-reasoning model based on the current operating status.
To resolve this fundamental problem, a causal model based representation framework for 'analogical reasoning' – searching and selecting the biological systems to apply – have been developed.
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Justyna Jupowicz-Kozak
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