New Model for Gas Well Loading Prediction

Author(s):  
Desheng Zhou ◽  
Hong Yuan
Keyword(s):  
Gas Well ◽  
2010 ◽  
Vol 25 (02) ◽  
pp. 172-181 ◽  
Author(s):  
Desheng Zhou ◽  
Hong Yuan
Keyword(s):  
Gas Well ◽  

2013 ◽  
Author(s):  
Zhong Hai-Quan ◽  
Liu Zhong-Neng ◽  
Liu Tong ◽  
Liang Kai ◽  
Ren Yong

Engineering ◽  
2014 ◽  
Vol 06 (08) ◽  
pp. 399-405
Author(s):  
Haiquan Zhong ◽  
Jiao Tan ◽  
Chi Zhang

2014 ◽  
Vol 1 (1) ◽  
pp. 14-20 ◽  
Author(s):  
Olafuyi Olalekan ◽  
◽  
Fadairo Adesina

2015 ◽  
Vol 26 ◽  
pp. 1530-1541 ◽  
Author(s):  
Adesina Fadairo ◽  
Falode Olugbenga ◽  
Nwosu Chioma Sylvia
Keyword(s):  
Gas Well ◽  

Author(s):  
H. Akabori ◽  
K. Nishiwaki ◽  
K. Yoneta

By improving the predecessor Model HS- 7 electron microscope for the purpose of easier operation, we have recently completed new Model HS-8 electron microscope featuring higher performance and ease of operation.


2005 ◽  
Vol 173 (4S) ◽  
pp. 140-141
Author(s):  
Mariana Lima ◽  
Celso D. Ramos ◽  
Sérgio Q. Brunetto ◽  
Marcelo Lopes de Lima ◽  
Carla R.M. Sansana ◽  
...  

Author(s):  
Thorsten Meiser

Stochastic dependence among cognitive processes can be modeled in different ways, and the family of multinomial processing tree models provides a flexible framework for analyzing stochastic dependence among discrete cognitive states. This article presents a multinomial model of multidimensional source recognition that specifies stochastic dependence by a parameter for the joint retrieval of multiple source attributes together with parameters for stochastically independent retrieval. The new model is equivalent to a previous multinomial model of multidimensional source memory for a subset of the parameter space. An empirical application illustrates the advantages of the new multinomial model of joint source recognition. The new model allows for a direct comparison of joint source retrieval across conditions, it avoids statistical problems due to inflated confidence intervals and does not imply a conceptual imbalance between source dimensions. Model selection criteria that take model complexity into account corroborate the new model of joint source recognition.


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