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Understanding Neural Networks and Fuzzy Logic: Basic Concepts and Applications
Stamatios V. Kartalopoulos,Stamatios V. Kartakapoulos +1 more
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TLDR
Understand the fundamentals of the emerging field of fuzzy neural networks, their applications and the most used paradigms with this carefully organized state-of-the-art textbook.Abstract:
From the Publisher:
Understand the fundamentals of the emerging field of fuzzy neural networks, their applications and the most used paradigms with this carefully organized state-of-the-art textbook. Previously tested at a number of noteworthy conference tutorials, the simple numerical examples presented in this book provide excellent tools for progressive learning. UNDERSTANDING NEURAL NETWORKS AND FUZZY LOGIC offers a simple presentation and bottom-up approach that is ideal for working professional engineers, undergraduates, medical/biology majors, and anyone with a nonspecialist background.Sponsored by:IEEE Neural Networks Councilread more
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Journal ArticleDOI
Active Hebbian learning algorithm to train fuzzy cognitive maps
TL;DR: This proposed learning procedure is a promising approach for exploiting experts' involvement with their subjective reasoning and at the same time improving the effectiveness of the FCM operation mode and thus it broadens the applicability of FCMs modeling for complex systems.
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Artificial neural network model for forecasting sub-hourly electricity usage in commercial buildings
TL;DR: In this paper, the authors presented a data-driven forecasting model for day-ahead electricity usage of buildings in 15-minute resolution by using variable importance analysis and selected key variables: day type indicator, time-of-day, HVAC set temperature schedule, outdoor air dry-bulb temperature, and outdoor humidity as the most important predictors for electricity consumption.
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Classification of heart rate data using artificial neural network and fuzzy equivalence relation
TL;DR: The heart rate variability is used as the base signal from which certain parameters are extracted and presented to the ANN for classification, and the same data is also used for fuzzy equivalence classifier.
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Modeling the mechanical behavior of fiber-reinforced polymeric composite materials using artificial neural networks—A review
TL;DR: This work is an attempt to reflect on the work done in the mechanical modeling of fiber-reinforced composite materials using ANN during the last decade.
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Evolutionary algorithms, simulated annealing and tabu search: a comparative study
TL;DR: A comparative study among GA, SA, and TS, which shows that these algorithms have many similarities, but they also possess distinctive features, mainly in their strategies for searching the solution state space.