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Wyświetlanie 1-2 z 2
Tytuł:
Comparison of linear interpolation and arctan approximation of one-dimensional monotonic utility functions based on experimental data
Autorzy:
Nikolova, N.
Tenekedjiev, K.
Dong, F.
Hirota, K.
Powiązania:
https://bibliotekanauki.pl/articles/969632.pdf
Data publikacji:
2009
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
utility function
interpolation
approximation
weighted least square
goodness-of-fit
statistical tests
Opis:
Elicitation of utilities is among the most time consuming tasks in decision analysis. We search for ways to shorten this phase without compromising the quality of results. We use the results from an empirical experiment with 104 participants. They elicited 9 inner nodes from their one-dimensional utility function over monetary gains and losses using three elicitation techniques. A specific feature of the results is their interval character, as the elicitators are fuzzy rational individuals. The data is used to construct arctan-approximated and linearly interpolated utilities and to compare the results. We form partial samples with 3, 4 and 5 nodes for each participant and each elicitation method, and again interpolate/approximate the utilities. We introduce goodness-of-fit and deterioration measures to analyze the decrease in quality of the utility function due to reduced data nodes. The analysis, using paired-sample tests, leads to the following conclusions: 1) arctan-approximation is more adequate than linear interpolation over the whole samples; 2) 5 inner nodes are sufficient to construct a satisfactory arctan-approximation; 3) arctan-approximation and linear interpolation are almost equal in quality over the partial samples, but the local risk aversion of the linearly interpolated utility function is of poor quality unlike that of the arctan-approximated utility function.
Źródło:
Control and Cybernetics; 2009, 38, 3; 835-861
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Iterative-interpolation algorithms for L2 model reduction
Autorzy:
Krajewski, W.
Viaro, U.
Powiązania:
https://bibliotekanauki.pl/articles/970959.pdf
Data publikacji:
2009
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
linear systems
model reduction
output-error minimization
L2 norm
Krylov subspaces
Arnoldi's algorithm
Opis:
This paper is concerned with the construction of reduced-order models for high-order linear systems in such a way that the L2 norm of the impulse-response error is minimized. Two convergent algorithms that draw on previous procedures presented by the same authors, are suggested: one refers to s-domain representations, the other to time-domain state-space representations. The algorithms are based on an iterative scheme that, at any step, satisfies certain interpolation constraints deriving from the optimality conditions. To make the algorithms suitable to the reduction of very large-scale systems, resort is made to Krylov subspaces and Arnoldi's method. The performance of the reduction algorithms is tested on two benchmark examples.
Źródło:
Control and Cybernetics; 2009, 38, 2; 543-554
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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