Results 161 to 170 of about 65,077 (195)

Uncertainty Quantification of Pareto Fronts

2020
Uncertainty quantification of Pareto fronts introduces new challenges connected to probabilities in infinite dimensional spaces. Indeed, Pareto fronts are, in general, manifolds belonging to infinite dimensional spaces: for instance, a curve in bi-objective optimization or a surface in three objective optimization. This article examines the methods for
Mohamed Bassi, Emmanuel Pagnacco, Roberta Lima, Eduardo Souza de Cursi   +3 more
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Ordinal classification using Pareto fronts

Expert Systems with Applications, 2015
We present an ordinal classification method using Pareto fronts.We define Pareto fronts describing class boundaries for a separable sample.We propose to predict the object class using the nearest Pareto front boundary.The proposed method is illustrated by a problem of IUCN Red List categorization.
M.M. Stenina, M.P. Kuznetsov, V.V. Strijov   +2 more
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Pareto Front Estimation Using Unit Hyperplane

2021
This work proposes a method to estimate the Pareto front even in areas without objective vectors in the objective space. For the Pareto front approximation, we use a set of non-dominated points, objective vectors, in the objective space. To finely approximate the Pareto front, we need to increase the number of objective vectors. It is worth to estimate
Tomoaki Takagi, Keiki Takadama, Hiroyuki Sato   +2 more
openaire   +1 more source

Statistics of Pareto Fronts

2019
We consider multiobjective optimization problems affected by uncertainty, where the objective functions or the restrictions involve random variables. We are interested in the evaluation of statistics such as medians, quantiles and confidence intervals for the Pareto front.
Mohamed Bassi, Emmanuel Pagnacco, Eduardo Souza de Cursi, Rachid Ellaia   +3 more
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Digital filter design using multiple Pareto fronts

Proceedings Third NASA/DoD Workshop on Evolvable Hardware. EH-2001, 2002
Evolutionary approaches have been used in a large variety of design domains, from aircraft engineering to the designs of analog filters. Many of these approaches use measures to improve the variety of solutions in the population. One such measure is clustering.
T. Schnier, X. Yao, P. Liu
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Pareto Fronts in Clinical Practice for Pinnacle

International Journal of Radiation Oncology*Biology*Physics, 2013
Our aim was to develop a framework to objectively perform treatment planning studies using Pareto fronts. The Pareto front represents all optimal possible tradeoffs among several conflicting criteria and is an ideal tool with which to study the possibilities of a given treatment technique.
Tomas, Janssen, Zdenko, van Kesteren, Gijs, Franssen, Eugène, Damen, Corine, van Vliet   +4 more
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Optimal Lossy Matching by Pareto Fronts

IEEE Transactions on Circuits and Systems II: Express Briefs, 2008
Although lossy matching is not a standard antenna matching technique, well-designed losses can facilitate wide-band matching of otherwise unmatchable antennas. The lossy matching designs developed in this paper are based on the Pareto front. These Pareto front computations permit the circuit designer to graphically select optimal gain-reflection ...
J.C. Allen, D. Arceo, P. Hansen
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Moving Along the Pareto Front

2009
A method to sort out the optimal solutions located along the Pareto front is proposed as a possible criterion of innovative design. The idea, in fact, is to investigate non-dominated solutions in a comparative way in view of a twofold scope: to help decision making, on one hand, and to identify previously unpredicted, innovative solutions, on the other
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Pareto-Front Exploitation in Symbolic Regression

2006
Symbolic regression via genetic programming (hereafter, referred to simply as symbolic regression) has proven to be a very important tool for industrial empirical modeling (Kotanchek et al., 2003). Two of the primary problems with industrial use of symbolic regression are (1) the relatively large computational demands in comparison with other nonlinear
Guido F. Smits, Mark Kotanchek
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Pareto-Front Exploration with Uncertain Objectives

2001
We consider the problem of exploration of the set of all global optima (Pareto-points) or an approximation thereof in the context of multi-objective function optimization. Up to now, set oriented techniques assume that the evaluation of the m-dimensional vector of objectives can be done exactly which is important to steer the search process towards ...
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