Uncertainty Measure for Quantum of Mass function

Author(s):  
Xiaozhuan Gao ◽  
Lipeng Pan ◽  
Yong Deng
2013 ◽  
Vol 329 ◽  
pp. 344-348
Author(s):  
Shao Pu Zhang ◽  
Tao Feng

Evidence theory is an effective method to deal with uncertainty information. And uncertainty measure is to reflect the uncertainty of an information system. Thus we want to merge evidence theory with uncertainty method in order to measure the roughness of a rough approximation space. This paper discusses the information fusion and uncertainty measure based on rough set theory. First, we propose a new method of information fusion based on the Bayse function, and define a pair of belief function and plausibility function using the fused mass function in an information system. Then we construct entropy for every decision class to measure the roughness of every decision class, and entropy for decision information system to measure the consistence of decision table.


Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Deyun Zhou ◽  
Yongchuan Tang ◽  
Wen Jiang

Uncertainty measure in data fusion applications is a hot topic; quite a few methods have been proposed to measure the degree of uncertainty in Dempster-Shafer framework. However, the existing methods pay little attention to the scale of the frame of discernment (FOD), which means a loss of information. Due to this reason, the existing methods cannot measure the difference of uncertain degree among different FODs. In this paper, an improved belief entropy is proposed in Dempster-Shafer framework. The proposed belief entropy takes into consideration more available information in the body of evidence (BOE), including the uncertain information modeled by the mass function, the cardinality of the proposition, and the scale of the FOD. The improved belief entropy is a new method for uncertainty measure in Dempster-Shafer framework. Based on the new belief entropy, a decision-making approach is designed. The validity of the new belief entropy is verified according to some numerical examples and the proposed decision-making approach.


2010 ◽  
Author(s):  
Marjolijn L. Antheunis ◽  
Patti M. Valkenburg ◽  
Jochen Peter
Keyword(s):  

2003 ◽  
Vol 6 ◽  
pp. 289-289
Author(s):  
A. Stolte
Keyword(s):  

1998 ◽  
Vol 508 (1) ◽  
pp. 347-369 ◽  
Author(s):  
K. L. Luhman ◽  
G. H. Rieke ◽  
C. J. Lada ◽  
E. A. Lada

2021 ◽  
Vol 502 (3) ◽  
pp. 3942-3954
Author(s):  
D Hung ◽  
B C Lemaux ◽  
R R Gal ◽  
A R Tomczak ◽  
L M Lubin ◽  
...  

ABSTRACT We present a new mass function of galaxy clusters and groups using optical/near-infrared (NIR) wavelength spectroscopic and photometric data from the Observations of Redshift Evolution in Large-Scale Environments (ORELSE) survey. At z ∼ 1, cluster mass function studies are rare regardless of wavelength and have never been attempted from an optical/NIR perspective. This work serves as a proof of concept that z ∼ 1 cluster mass functions are achievable without supplemental X-ray or Sunyaev-Zel’dovich data. Measurements of the cluster mass function provide important contraints on cosmological parameters and are complementary to other probes. With ORELSE, a new cluster finding technique based on Voronoi tessellation Monte Carlo (VMC) mapping, and rigorous purity and completeness testing, we have obtained ∼240 galaxy overdensity candidates in the redshift range 0.55 < z < 1.37 at a mass range of 13.6 < log (M/M⊙) < 14.8. This mass range is comparable to existing optical cluster mass function studies for the local universe. Our candidate numbers vary based on the choice of multiple input parameters related to detection and characterization in our cluster finding algorithm, which we incorporated into the mass function analysis through a Monte Carlo scheme. We find cosmological constraints on the matter density, Ωm, and the amplitude of fluctuations, σ8, of $\Omega _{m} = 0.250^{+0.104}_{-0.099}$ and $\sigma _{8} = 1.150^{+0.260}_{-0.163}$. While our Ωm value is close to concordance, our σ8 value is ∼2σ higher because of the inflated observed number densities compared to theoretical mass function models owing to how our survey targeted overdense regions. With Euclid and several other large, unbiased optical surveys on the horizon, VMC mapping will enable optical/NIR cluster cosmology at redshifts much higher than what has been possible before.


1998 ◽  
Vol 11 (1) ◽  
pp. 423-424
Author(s):  
Motohide Tamura ◽  
Yoichi Itoh ◽  
Yumiko Oasa ◽  
Alan Tokunaga ◽  
Koji Sugitani

Abstract In order to tackle the problems of low-mass end of the initial mass function (IMF) in star-forming regions and the formation mechanisms of brown dwarfs, we have conducted deep infrared surveys of nearby molecular clouds. We have found a significant population of very low-luminosity sources with IR excesses in the Taurus cloud and the Chamaeleon cloud core regions whose extinction corrected J magnitudes are 3 to 8 mag fainter than those of typical T Tauri stars in the same cloud. Some of them are associated with even fainter companions. Follow-up IR spectroscopy has confirmed for the selected sources that their photospheric temperature is around 2000 to 3000 K. Thus, these very low-luminosity young stellar sources are most likely very low-mass T Tauri stars, and some of them might even be young brown dwarfs.


2019 ◽  
Vol 15 (S359) ◽  
pp. 386-390
Author(s):  
Lucimara P. Martins

AbstractWith the exception of some nearby galaxies, we cannot resolve stars individually. To recover the galaxies star formation history (SFH), the challenge is to extract information from their integrated spectrum. A widely used tool is the full spectral fitting technique. This consists of combining simple stellar populations (SSPs) of different ages and metallicities to match the integrated spectrum. This technique works well for optical spectra, for metallicities near solar and chemical histories not much different from our Galaxy. For everything else there is room for improvement. With telescopes being able to explore further and further away, and beyond the optical, the improvement of this type of tool is crucial. SSPs use as ingredients isochrones, an initial mass function, and a library of stellar spectra. My focus are the stellar libraries, key ingredient for SSPs. Here I talk about the latest developments of stellar libraries, how they influence the SSPs and how to improve them.


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