Results 261 to 270 of about 3,570,719 (299)

Constrained implicit function fitting

[1992] Proceedings. 11th IAPR International Conference on Pattern Recognition, 2003
Describes techniques for stabilizing the implicit function fitting process. The key drawback of implicit function fitting methods described in literature thus far has been the stability with respect to outliners in the data. In this paper methods for stabilizing the implicit function fitting using additional constraints in the form of surface (curve ...
Gabriel Taubin, Ruud M. Bolle, Baba C. Vemuri   +2 more
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A guide for fitness function design

Proceedings of the 13th annual conference companion on Genetic and evolutionary computation, 2011
Fitness function design is often both a design and performance bottleneck for evolutionary algorithms. The fitness function for a given problem is directly related to the specifications for that problem. This paper outlines a guide for transforming problem specifications into a fitness function.
Josh L. Wilkerson, Daniel R. Tauritz
openaire   +1 more source

Fitness, aging and neurocognitive function

Neurobiology of Aging, 2005
In this manuscript we provide a brief review of the recent literature that has examined the relationship among fitness training, cognition and brain. We began with a discussion of the non-human animal literature that has examined the relationship among these factors.
Arthur F, Kramer, Stanley J, Colcombe, Edward, McAuley, Paige E, Scalf, Kirk I, Erickson   +4 more
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Nonpolynomial fitting of multiparameter functions

Physical Review E, 1996
A stochastic self-regulating simulated annealing optimization method is presented, and compared to other optimization methods such as the simplex, steepest descent, and the recently proposed fast fitting method by Penna [Phys. Rev. E 51, R1 (1995)].
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Testing the Fit of a Parametric Function

Journal of the American Statistical Association, 1999
General methods for testing the fit of a parametric function are proposed. The idea underlying each method is to "accept" the prescribed parametric model if and only if it is chosen by a model selection criterion. Several different selection criteria are considered, including one based on a modified version of the Akaike information criterion and ...
Aerts, M., Claeskens, G.A.M., Hart, J.D.
openaire   +1 more source

Boolean Functions Fitness Spaces

1999
We investigate the distribution of performance of the Boolean functions of 3 Boolean inputs (particularly that of the parity functions), the always-on-6 and even-6 parity functions. We use enumeration, uniform Monte-Carlo random sampling and sampling random full trees. As expected XOR dramatically changes the fitness distributions.
William B. Langdon, Riccardo Poli
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Profile Fitting by the Interference Function

Advances in X-ray Analysis, 1991
AbstractOn the basis of the “column-like” powder model of Warren and Averbach, a profile fitting procedure was devised to obtain microstructural disorder parameters. The interference functionwhere d is the interplanar distance, λ the wavelength, θ the diffraction angle and N the number of cells within a column, was used to model experimental profiles ...
Lutterotti, Luca, Scardi, Paolo
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Function and Fitness

2016
This chapter focuses on the fitness-contribution theory of function, which holds, roughly, that the function of a trait consists in its typical contribution to the fitness of the organisms that possess it. I begin by surveying several different theories within this family, and I show why any plausible version must include a statistical element.
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Fitting Density Functions with Polynomials

Applied Statistics, 1992
Summary: A robust procedure is developed for estimating density functions from data. It requires the existence of a parametric function, called the key function, to give a first approximation to the density and then improves the fit using polynomial adjustments.
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Evolutionary Neuroestimation of Fitness Functions

2003
One of the most influential factors in the quality of the solutions found by an evolutionary algorithm is the appropriateness of the fitness function. Specifically in data mining, in where the extraction of useful information is a main task, when databases have a great amount of examples, fitness functions are very time consuming.
Jesús S. Aguilar-Ruiz, Daniel Mateos, Domingo S. Rodríguez   +2 more
openaire   +1 more source