2020
DOI: 10.1109/tfuzz.2020.2969384
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An Optimized Type-2 Self-Organizing Fuzzy Logic Controller Applied in Anesthesia for Propofol Dosing to Regulate BIS

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Cited by 23 publications
(8 citation statements)
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“…In particular fuzzy rule based inference systems have been most commonly used for decision making and control applications, [17,18], while indoor video monitoring and other video analytics tasks are also accomplished using fuzzy logic systems [19,20].…”
Section: Background Concepts Of Fuzzy Logicmentioning
confidence: 99%
See 1 more Smart Citation
“…In particular fuzzy rule based inference systems have been most commonly used for decision making and control applications, [17,18], while indoor video monitoring and other video analytics tasks are also accomplished using fuzzy logic systems [19,20].…”
Section: Background Concepts Of Fuzzy Logicmentioning
confidence: 99%
“…Type-1 Fuzzy Sets are only able to compute a crisp membership value with respect to the degree of membership of a data point to that set. A type-2 fuzzy set is characterized by a fuzzy membership function, where the computed membership value for a data point is itself a fuzzy set in [0, 1] represented by a secondary membership function with secondary membership grades projected in a separate dimension [18,23]. This enables the fuzzy sets to have additional design degrees of freedom that can capture rich information and handle higher orders of uncertainties associated with the data point being processed.…”
Section: Background Concepts Of Fuzzy Logicmentioning
confidence: 99%
“…FL is an approach where numerical data is quantified into linguistic terms (fuzzy sets) that can account for inherent noise or uncertainties in real-world data (IoT sensor values, subjective opinions of commuters). Together with the use of If-Then rules, FL can facilitate approximate reasoning and inference for producing interpretable decision-making and control systems (Alhabashneh et al 2017;Wei et al 2020). EAs enable the modeling of stochastic systems based on the process of natural selection using techniques such as genetic algorithms, genetic programming, and swarm intelligence optimization algorithms (Dreier 2002;Parpinelli and Lopes, 2011;Poli et al 2008).…”
Section: Artificial Intelligence Solutions For Smart Citesmentioning
confidence: 99%
“…The application of fuzzy logic theory provides an effective way to deal with the approximate and inexact nature of the real world 21,22 . Fuzzy logic control has been used to design control strategy in industrial process control, biomedical research, pattern recognition, and other fields 23‐25 . For the sake of completing a general fuzzy logic control, each of the components, that is, a fuzzification part, an inference engine and a defuzzification part have to be implemented 26 .…”
Section: Introductionmentioning
confidence: 99%