Intuitionistic fuzzy estimation and generalized net model of e-learning within a university local network

In recent years, several researchers have proposed many fuzzy inference systems for learners' learning progress inference and evaluation. Fuzzy logic-based knowledge representation provides a functional way that achieves to capture and infer from even lexically imprecise and/or uncertain meanings of everyday type facts within the learning process. Part III begins with this introductory chapter that connects the fuzzy with educational world, presenting a review of fuzzy logic-based methodologies/applications related with the education domain. The main methodological approaches presented in Part II, such as Fuzzy Inference System (FIS), Adaptive Neuro-Fuzzy Inference System (ANFIS), Intuitionistic Fuzzy Inference System (IFIS), and Fuzzy Cognitive Map (FCM), are considered here from their functionality within the learning context, as a means to better understand the coexistence of both worlds. Analytical fuzzy logic-based applications and in-depth exploitation of the way each one is placed within the educational context are presented in the rest chapters of Part III.

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Intuitionistic fuzzy estimation and generalized net model of e-learning within a university local network

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Modeling of Buck DC-to-DC Converter with Generalized Nets

Modeling of Buck DC-to-DC Converter with Generalized Nets

Connecting the Educational and Fuzzy Worlds

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