K
Karla Figueiredo
Researcher at Rio de Janeiro State University
Publications - 55
Citations - 265
Karla Figueiredo is an academic researcher from Rio de Janeiro State University. The author has contributed to research in topics: Reinforcement learning & Neuro-fuzzy. The author has an hindex of 7, co-authored 53 publications receiving 202 citations. Previous affiliations of Karla Figueiredo include Pontifical Catholic University of Rio de Janeiro & Federal University of Rio de Janeiro.
Papers
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Proceedings ArticleDOI
Irregularity detection on low tension electric installations by neural network ensembles
Cyro Muniz,Karla Figueiredo,Marley M. B. R. Vellasco,Gustavo Chavez,Marco Aurélio Cavalcanti Pacheco +4 more
TL;DR: The proposal of an intelligent system, composed of two neural networks ensembles, which intends to increase the level of accuracy in the identification of irregularities among low tension consumers, is presented.
Proceedings Article
A Neuro-fuzzy System for Fraud Detection in Electricity Distribution.
TL;DR: A combined approach of a neural networks committee and a neuro-fuzzy hierarchical system intended to increase the level of accuracy in the identification of irregularities among low voltage consumers is presented.
Journal ArticleDOI
Intelligent multiagent coordination based on reinforcement hierarchical neuro-fuzzy models.
TL;DR: Two new models of coordination for intelligent multiagent systems are developed, which integrates the Reinforcement Learning Hierarchical Neuro-Fuzzy model with two proposed coordination mechanisms that greatly improve the performance of the multiagent system when compared with other strategies.
Journal ArticleDOI
A Portable Fuzzy Driver Drowsiness Estimation System.
TL;DR: This research proposes the development of a new portable, low-cost, accurate, and robust drowsiness recognition device that was assessed in terms of its computational performance and efficiency, resulting in a significant accuracy of 95.5% in state recognition that demonstrates the feasibility of the approach.
Journal ArticleDOI
Multi-agent systems with reinforcement hierarchical neuro-fuzzy models
TL;DR: This paper introduces a new multi- agent model for intelligent agents, called reinforcement learning hierarchical neuro-fuzzy multi-agent system, which uses a hierarchical partitioning of the input space with a reinforcement learning algorithm to overcome limitations of previous RL methods.