scholarly journals Projection-based statistical analysis of full-chip leakage power with non-log-normal distributions

Author(s):  
Xin Li ◽  
Jiayong Le ◽  
L.T. Pileggi
Author(s):  
Lingshuang Kong ◽  
Zude Cao ◽  
Sheng Dong

The connection of wind and channel siltation is derived. Coefficient of the equation is ascertained using observed data. The annual maximal sudden siltation of channel of 1979∼2003 of Huanghua harbor is calculated using the derived formula and statistical analysis is carried out. The P-III type and Log-normal distributions are used to compute the return period of siltation amount.


1984 ◽  
Vol 93 (6) ◽  
pp. 591-598 ◽  
Author(s):  
Sandeep K Malhotra

2019 ◽  
Vol 19 (8) ◽  
pp. 1685-1702 ◽  
Author(s):  
Juan José Martín-Sotoca ◽  
Antonio Saa-Requejo ◽  
Rubén Moratiel ◽  
Nicolas Dalezios ◽  
Ioannis Faraslis ◽  
...  

Abstract. Vegetation indices based on satellite images, such as the normalized difference vegetation index (NDVI), have been used in countries like the USA, Canada and Spain for damaged pasture and forage insurance over the last few years. This type of agricultural insurance is called satellite-index-based insurance (SIBI). In SIBI, the occurrence of damage is defined as normal distributions. In this work a pasture area at the north of the Community of Madrid (Spain) has been delimited by means of Moderate Resolution Imaging Spectroradiometer (MODIS) images. A statistical analysis of NDVI histograms was applied to seek for alternative distributions using the maximum likelihood method and χ2 test. The results show that the normal distribution is not the optimal representation and the generalized extreme value (GEV) distribution presents a better fit through the year based on a quality estimator. A comparison between normal and GEV is shown with respect to the probability under a NDVI threshold value throughout the year. This suggests that an a priori distribution should not be selected and a percentile methodology should be used to define a NDVI damage threshold rather than the average and standard deviation, typically of normal distributions. Highlights. The GEV distribution provides better fit to the NDVI historical observations than the normal one. Differences between normal and GEV distributions are higher during spring and autumn, which are transition periods in the precipitation regimen. NDVI damage threshold shows evident differences using normal and GEV distributions both covering the same probability (24.20 %). NDVI damage threshold values based on percentile calculation are proposed as an improvement in the index-based insurance in damaged pasture.


2019 ◽  
Vol 1338 ◽  
pp. 012036
Author(s):  
D Kurniasari ◽  
R Widyarini ◽  
Warsono ◽  
Y Antonio

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