A comparison between drop size distributions derived from the probability distribution functions and maximum entropy principle. Case study; pilot plant Scheibel extraction column

2017 ◽  
Vol 117 ◽  
pp. 648-658 ◽  
Author(s):  
Mehdi Asadollahzadeh ◽  
Rezvan Torkaman ◽  
Meisam Torab-Mostaedi ◽  
Jaber Safdari
Keyword(s):  
Probability Distribution ◽  
Drop Size ◽  
Maximum Entropy Principle ◽  
Distribution Functions ◽  
Extraction Column ◽  
Size Distributions ◽  
Probability Distribution Functions ◽  
Entropy Principle ◽  
Drop Size Distributions

Using maximum entropy approach for prediction of drop size distribution in a pilot plant multi-impeller extraction contactor

RSC Advances ◽  
2015 ◽  
Vol 5 (116) ◽  
pp. 95967-95980 ◽  
Author(s):  
Mehdi Asadollahzadeh ◽  
Meisam Torab-Mostaedi ◽  
Shahrokh Shahhosseini ◽  
Ahad Ghaemi
Keyword(s):  
Maximum Entropy ◽  
Size Distribution ◽  
Pilot Plant ◽  
Drop Size ◽  
Maximum Entropy Principle ◽  
Drop Size Distribution ◽  
Size Distributions ◽  
Entropy Principle ◽  
Drop Size Distributions ◽  
Column Extractor

In this study, the maximum entropy principle is used to predict the drop size distributions in a multi-impeller column extractor.

scholarly journals Time-Based Modeling of Linguistic Preference to Preferential Probability

2011 ◽  
Author(s):  
Andy Dong ◽  
Tomonori Honda ◽  
Maria C. Yang
Keyword(s):  
Probability Distribution ◽  
Natural Language ◽  
State Transition ◽  
Distribution Functions ◽  
Time Varying ◽  
Transition Matrices ◽  
Probability Distribution Functions ◽  
Semantic Resources ◽  
Model Preference

In this paper, we present a method to estimate the likely concept a committee of designers will select given their verbalized preferences toward each alternative. In order to perform this estimation, we present a new method of preference elicitation based on natural language. First, we show a way to model preference in the natural language of appraisal, which describes the degree of intensity and the uncertainty of preference based upon gradable semantic resources to express appraisals. We then show a way to map linguistic appraisals into probability distribution functions. Finally, we present a Markov model that utilizes these probability distribution functions in state transition matrices to calculate in a time-varying manner the change of preference over time. We present a case study to illustrate the validity of the method.

scholarly journals Performance Probability Distribution Function for Modelling Solar Radiation in South Southern Nigeria: A Case Study of Yenagoa

2019 ◽  
pp. 1-8
Author(s):  
Chukwutem Isaac Abiodun ◽  
Obiora Emeka Anisiji
Keyword(s):  
Distribution Function ◽  
Probability Distribution ◽  
Solar Radiation ◽  
Probability Distribution Function ◽  
Distribution Functions ◽  
Logistic Distribution ◽  
Scale Parameters ◽  
Probability Distribution Functions ◽  
Statistical Distribution Function

This study has attempted to assess the performance of the most suitable statistical distribution function for modelling solar radiation over Yenagoa, Bayelsa State in Nigeria. The probability distribution functions are tested based on eleven years (2007-2017) solar radiation data obtained from National Aeronautics and Space Administration (NASA). Six probability distribution functions are tested to ascertain the most appropriate one based on four different statistical tools and fitting accuracy. The associated parameters of the most appropriate fitted probability distribution function are calculated and the trends in the characteristic of the solar radiation are deduced. The result shows that logistic distribution presents the most suitable probability distribution function for modelling solar radiation over the selected environment with RMSE of 1.500 KWh/m2/day, MAE of 1.260 KWh/m2/day, MAPE of 22.000% and R2 of 0.880.When compared with the other five distribution functions, the same trend could be seen although with different values of RMSE, MAE, MAPE and R2. The estimated distribution location and scale parameters of the model vary with month and season. The overall result will be useful for predicting future solar radiation over the studied environment. It will also be a good reference point for the design of large solar power projects in Yenagoa in particular and south southern Nigerian environments  at large.

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