Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Carlos R. B. Azevedo"'
Publikováno v:
IEEE Transactions on Cybernetics. 46:778-791
In several applications, a solution must be selected from a set of tradeoff alternatives for operating in dynamic and noisy environments. In this paper, such multicriteria decision process is handled by anticipating flexible options predicted to impr
Autor:
Carlos R. B. Azevedo, Rodrigo Ignacio R. Gonzalez, Rafia Inam, João Batista Camargo, Jorge Rady de Almeida, Jamil K. Naufal, C. B. S. T. Molina, Lucio F. Vismari
Publikováno v:
Safety and Reliability – Theory and Applications.
Publikováno v:
Safety and Reliability – Theory and Applications.
Publikováno v:
CogSIMA
Human-machine interactions are likely to require synergistic multidisciplinary research efforts for supporting a paradigm shift towards collaborative-oriented use cases. An essential aspect of collaboration is trust and in order to establish it there
Publikováno v:
Anais do 10. Congresso Brasileiro de Inteligência Computacional.
Portfolio Optimization (PO) is a resource allocation problem where real valued weights are assigned to multiple financial assets in order to maximize the return and minimize the risk. The Memetic Tree-based Algorithm (MTGA), employing a tree represen
Autor:
Carlos R. B. Azevedo, Tiago A. E. Ferreira, Waslon T. A. Lopes, Francisco Madeiro, Renan Araujo Azevedo, Esdras L. Bispo Júnior
Publikováno v:
Learning and Nonlinear Models. 6:3-15
Publikováno v:
IEEE Congress on Evolutionary Computation
This paper proposes a regularized hypervolume (SMetric) selection algorithm. The proposal is used for incorporating stability and diversification in financial portfolios obtained by solving a temporal sequence of multi-objective Mean Variance Problem
Anticipatory Stochastic Multi-Objective Optimization for uncertainty handling in portfolio selection
Publikováno v:
IEEE Congress on Evolutionary Computation
An anticipatory stochastic multi-objective model based on S-Metric maximization is proposed. The environment is assumed to be noisy and time-varying. This raises the question of how to incorporate anticipation in metaheuristics such that the Pareto o
Autor:
André R. Gonçalves, Salomao Madeiro, Carlos R. B. Azevedo, Rosana Veroneze, Fernando J. Von Zuben
Publikováno v:
Artificial Neural Networks and Machine Learning – ICANN 2012 ISBN: 9783642332654
ICANN (2)
ICANN (2)
Several clustering algorithms have been considered to determine the centers and dispersions of the hidden layer neurons of Radial Basis Function Neural Networks (RBFNNs) when applied both to regression and classification tasks. Most of the proposed a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::526f1bc70a35aee2f6a724f66ebc754f
https://doi.org/10.1007/978-3-642-33266-1_19
https://doi.org/10.1007/978-3-642-33266-1_19
Publikováno v:
IEEE Congress on Evolutionary Computation
The insertion of atypical solutions (immigrants) in Evolutionary Algorithms populations is a well studied and successful strategy to cope with the difficulties of tracking optima in dynamic environments in single-objective optimization. This paper st