F
Fernando J. Von Zuben
Researcher at State University of Campinas
Publications - 235
Citations - 3898
Fernando J. Von Zuben is an academic researcher from State University of Campinas. The author has contributed to research in topics: Artificial immune system & Artificial neural network. The author has an hindex of 32, co-authored 229 publications receiving 3665 citations.
Papers
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Book ChapterDOI
aiNet: An Artificial Immune Network for Data Analysis
TL;DR: This chapter shows that some of the basic aspects of the natural immune system discussed in the previous chapter can be used to propose a novel artificial immune network model with the main goals of clustering and filtering crude data sets described by high-dimensional samples.
MonographDOI
Recent Developments In Biologically Inspired Computing
TL;DR: This book covers the most relevant areas in computational intelligence, including evolutionary algorithms, artificial neural networks, artificial immune systems and swarm systems, and brings together novel and philosophical trends in the exciting fields of artificial life and robotics.
Proceedings ArticleDOI
An artificial immune network for multimodal function optimization on dynamic environments
TL;DR: Dopt-aiNet, an immune-inspired version for dynamic optimization of multimodal optimization algorithms inspired by the immune system, is extended here to deal with time-varying fitness functions.
Journal ArticleDOI
Vox Populi: An Interactive Evolutionary System for Algorithmic Music Composition
TL;DR: Vox Populi is a system based on evolutionary computation techniques for composing music in real time that evolves through the application of genetic algorithms to maximize a fitness criterion based on physical factors relevant to music.
Journal ArticleDOI
Switch allocation problems in power distribution systems
Laura Silva de Assis,José Federico Vizcaı´no González,Fábio Luiz Usberti,Christiano Lyra,Celso Cavellucci,Fernando J. Von Zuben +5 more
TL;DR: In this paper, an optimization methodology to allocate switches on radially operated distribution networks is proposed to minimize the costs of allocation and energy not supplied, under reliability and flow capacity constraints.