A statistical methodology to identify imbalance-induced capacity wastes for LV networks

2021 ◽  
Vol 199 ◽  
pp. 107388
Author(s):  
Lurui Fang ◽  
Kang Ma ◽  
Zhong Zhang
2016 ◽  
Author(s):  
Maia Hurley ◽  
Jeff Schneider ◽  
Eric Falk ◽  
Carole Massey ◽  
David McGrath ◽  
...  

2018 ◽  
Vol 4 ◽  
pp. 26 ◽  
Author(s):  
Brieuc Voirin ◽  
Grégoire Kessedjian ◽  
Abdelaziz Chebboubi ◽  
Sylvain Julien-Laferrière ◽  
Olivier Serot

Studies on fission yields have a major impact on the characterization and the understanding of the fission process and are mandatory for reactor applications. Fission yield evaluation represents the synthesis of experimental and theoretical knowledge to perform the best estimation of mass, isotopic and isomeric yields. Today, the output of fission yield evaluation is available as a function of isotopic yields. Without the explicitness of evaluation covariance data, mass yield uncertainties are greater than those of isotopic yields. This is in contradiction with experimental knowledge where the abundance of mass yield measurements is dominant. These last years, different covariance matrices have been suggested but the experimental part of those are neglected. The collaboration between the LPSC Grenoble and the CEA Cadarache starts a new program in the field of the evaluation of fission products in addition to the current experimental program at Institut Laue-Langevin. The goal is to define a new methodology of evaluation based on statistical tests to define the different experimental sets in agreement, giving different solutions for different analysis choices. This study deals with the thermal neutron induced fission of 235U. The mix of data is non-unique and this topic will be discussed using the Shannon entropy criterion in the framework of the statistical methodology proposed.


1952 ◽  
Vol 16 (4) ◽  
pp. 480
Author(s):  
William O. Jones ◽  
Oscar Krisen Buros

2003 ◽  
Vol 319 ◽  
pp. 591-600 ◽  
Author(s):  
Lluis nindexLligonaLligoña Trulla ◽  
Joseph P. Zbilut ◽  
Alessandro Giuliani

Diagnostics ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 162
Author(s):  
Werner Vach ◽  
Oke Gerke

Measurement procedures are not error-free. Potential users of a measurement procedure need to know the expected magnitude of the measurement error in order to justify its use, in particular in health care settings. Gold standard procedures providing exact measurements for comparisons are often lacking. Consequently, scientific investigations of the measurement error are often based on using replicates. However, a standardized terminology (and partially also methodology) for such investigations is lacking. In this paper, we explain the basic conceptual approach of such investigations with minimal reference to existing terminology and describe the link to the existing general statistical methodology. This way, some of the key measures used in such investigations can be explained in a simple manner and some light can be shed on existing terminology. We encourage clearly conceptually distinguishing between investigations of the measurement error of a single measurement procedure and the comparison between different measurement procedures or observers. We also identify an unused potential for more advanced statistical analyses in scientific investigations of the measurement error.


2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Katerina G. Tsakiri ◽  
Antonios E. Marsellos ◽  
Igor G. Zurbenko

Flooding normally occurs during periods of excessive precipitation or thawing in the winter period (ice jam). Flooding is typically accompanied by an increase in river discharge. This paper presents a statistical model for the prediction and explanation of the water discharge time series using an example from the Schoharie Creek, New York (one of the principal tributaries of the Mohawk River). It is developed with a view to wider application in similar water basins. In this study a statistical methodology for the decomposition of the time series is used. The Kolmogorov-Zurbenko filter is used for the decomposition of the hydrological and climatic time series into the seasonal and the long and the short term component. We analyze the time series of the water discharge by using a summer and a winter model. The explanation of the water discharge has been improved up to 81%. The results show that as water discharge increases in the long term then the water table replenishes, and in the seasonal term it depletes. In the short term, the groundwater drops during the winter period, and it rises during the summer period. This methodology can be applied for the prediction of the water discharge at multiple sites.


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