Even FIB Decomposition Model Based on Storage and Traffic Balancing

2017 ◽  
Vol 26 (4) ◽  
pp. 681-687
Author(s):  
Wenlong Chen ◽  
Shuxian Wang ◽  
Xiaolan Tang ◽  
Lijing Lan
Keyword(s):  
Decomposition Model ◽  
Model Based ◽  
Traffic Balancing

An iterative method for tomographic x-ray perfusion estimation in a decomposition model-based approach

2010 ◽  
Vol 37 (12) ◽  
pp. 6125-6141 ◽  
Author(s):  
Christoph Neukirchen ◽  
Marco Giordano ◽  
Steffen Wiesner
Keyword(s):  
Iterative Method ◽  
X Ray ◽  
Decomposition Model ◽  
Model Based

scholarly journals Non-intrusive load decomposition model based on Group Bayesian optimization and post-processing

2021 ◽  
Vol 252 ◽  
pp. 03007
Author(s):  
Tan Zhukui ◽  
Liu Bin ◽  
Zhang Qiuyan ◽  
Ding Chao ◽  
Hu Houpeng
Keyword(s):  
Power Consumption ◽  
Computational Cost ◽  
Optimization Method ◽  
Bayesian Optimization ◽  
Post Processing ◽  
Data Set ◽  
Decomposition Model ◽  
Model Based ◽  
Public Data ◽  
Load Decomposition

Non-intrusive load decomposition can decompose the power consumption of a single appliance from the household bus data, which is of great significance for users to adjust their own power consumption strategy. In order to solve the problem of large amount of computation in hyperparameter optimization of load decomposition model based on deep residual network, a Group Bayesian optimization method is proposed. This method can obtain better hyperparameter combination with less computational cost. In addition, in order to solve the problem of irrelevant activation of the model decomposition results, an improved post-processing method is proposed to improve the comprehensive performance of the model. Finally, the public data set REFIT is used to verify the proposed method, and the results show that the proposed method has a low decomposition error.

A New Improved Decomposition Model Based on Laspeyres Index: A Case of CO2 Emission in China from 1996-2011

2013 ◽  
Vol 734-737 ◽  
pp. 1797-1803 ◽  
Author(s):  
Li Ning Wang ◽  
Ding Ma ◽  
Wen Ying Chen
Keyword(s):  
Time Series ◽  
Decomposition Methods ◽  
Related Factors ◽  
Decomposition Model ◽  
Model Based ◽  
Laspeyres Index ◽  
Discrete Change ◽  
Empirical Illustration

Due to some drawbacks of the Divisia inedex and its relevant decomposition methods, such as difficult affording accurate estimations in period-wise and cross-region decompositions with large discrete change data and involving logarithmic calculations. This paper introduces a new decomposition index based on Laspeyres index (LI), leaving no unexplained residuals. It distributes interactive term among related factors according to different contribution rates of each factor which are related to the changes of these factors. An empirical illustration, decomposing changes in CO2emissions in China from 1996 to 2011 by both the proposed method (WLI) and Sun's Laspeyres index (SLI) methods time-series and period-wise methods, is carried out.

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