Titlebook: Evolutionary Design of Intelligent Systems in Modeling, Simulation and Control; Oscar Castillo,Witold Pedrycz,Janusz Kacprzyk Book 2009 Sp

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A Hybrid Recommender System Architecture for Learning Objectsle. We propose a hybrid recommender system that uses collaborative filtering techniques together with fuzzy inference systems to provide recommendations, considering the instructor’s experience as well as the ratings given by similar students.

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Book 2009on and c- trol. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and evolutionary algorithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in four main parts, which contain a group of papers ar

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Hybrid Interval Type-1 Non-singleton Type-2 Fuzzy Logic Systems Are Type-2 Adaptive Neuro-fuzzy Infeill (HSM) and used to predict the transfer bar surface temperature at finishing Scale Breaker (SB) entry zone. Comparative results show the performance of the hybrid learning method (RLS-BP) against the only BP learning.

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Kidnap

TA-Fuzzy Semantic Networks for Interaction Representation in Social Simulationrepresents a society with differences between individuals. Our proposal is to combine fuzzy logic, semantic networks and transactional analysis for representation of social interactions, taking into account the perception and a psychosocial profile of each individual. This model will facilitate the implementation of socially intelligent agents.

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Controlling Unstable Non-Minimum-Phase Systems with Fuzzy Logic: The Perturbed Case used in a PD FLC to regulate a plant consisting in a non-minimum-phase servomechanism with nonlinear backlash. Simulations demonstrate that the proposed FLC can be used to handle the non-minimum-phase systems.

Tremor

Genetic Optimization for the Design of Walking Patterns of a Biped Robotobot to obtain periodic motions while fulfills a minimal energy consumption over a complete walking cycle assumed as single support and instantaneous double support phases. Optimization results are presented showing walking patterns with low energy consumption and periodic motions.