Fuzzy sets as a basis for a theory of possibility
Fuzzy Sets and Systems
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part I
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In order to minimize the costs and maximize its efficiency, a Sequencing Batch Reactor requires continuous monitoring. The sensors it can be reasonably equipped with provide only indirect information on the state of the chemical reactions taking place in the tank, so the data must be analysed and interpreted. At present, no optimum, completely reliable procedure exists: instead, there exist several criteria which can be applied under different conditions. This paper shows that estimating the confidence in the quality of the response of a criterion can increase the robustness of a criterion. Then, interpreting the responses in terms of possibility distributions, the different answers can be merged, thus obtaining a more reliable overall estimate.