scholarly journals Estimation of the COCOMO Model Parameters Using Genetic Algorithms for NASA Software Projects

2006 ◽  
Vol 2 (2) ◽  
pp. 118-123 ◽  
Author(s):  
Alaa F. Sheta
Author(s):  
Roger C. von Doenhoff ◽  
Robert J. Streifel ◽  
Robert J. Marks

Abstract A model of the friction characteristics of carbon brakes is proposed to aid in the understanding of the causes of brake vibration. The model parameters are determined by a genetic algorithm in an attempt to identify differences in friction properties between brake applications during which vibration occurs and those during which there is no vibration. The model computes the brake torque as a function of wheelspeed, brake pressure, and the carbon surface temperature. The surface temperature is computed using a five node temperature model. The genetic algorithm chooses the model parameters to minimize the error between the model output and the torque measured during a dynamometer test. The basics of genetic algorithms and results of the model parameter identification process are presented.


Author(s):  
Sherry Chalotra ◽  
S. K. Sehra ◽  
Y. S. Brar ◽  
Navdeep Kaur

Author(s):  
Soo Ling Lim ◽  
Mark Harman ◽  
Angelo Susi

Large software projects have many stakeholders. In order for the resulting software system and architecture to be aligned with the enterprise and stakeholder needs, key stakeholders must be adequately consulted and involved in the project. This work proposes the use of genetic algorithms to identify key stakeholders and their actual influence in requirements elicitation, given the stakeholders’ requirements and the actual set of requirements implemented in the project. The proposed method is applied to a large real-world software project. Results show that search is able to identify key stakeholders accurately. Results also indicate that many different good solutions exist. This implies that a stakeholder has the potential to play a key role in requirements elicitation, depending on which other stakeholders are already involved. This work demonstrates the true complexity of requirements elicitation – all stakeholders should be consulted, but not all of them should be treated as key stakeholders, even if they appear to be significant based on their role in the domain.


2015 ◽  
pp. 1125-1152
Author(s):  
Tania Pencheva ◽  
Maria Angelova ◽  
Krassimir Atanassov

Intuitionistic fuzzy logic has been implemented in this investigation aiming to derive intuitionistic fuzzy estimations of model parameters of yeast fed-batch cultivation. Considered here are standard simple and multi-population genetic algorithms as well as their modifications differ from each other in execution order of main genetic operators (selection, crossover, and mutation). All are applied for the purpose of parameter identification of S. cerevisiae fed-batch cultivation. Performances of the examined algorithms have been assessed before and after the application of a procedure for narrowing the range of model parameters variation. Behavior of standard simple genetic algorithm has been also examined for different values of proof as the most sensitive genetic algorithms parameter toward convergence time, namely, generation gap (GGAP). Results obtained after the intuitionistic fuzzy logic implementation for assessment of genetic algorithms performance have been compared. As a result, the most reliable algorithm/value of GGAP ensuring the fastest and the most valuable solution is distinguished.


ETRI Journal ◽  
2000 ◽  
Vol 22 (1) ◽  
pp. 38-46 ◽  
Author(s):  
Ilgu Yun Yun ◽  
Lawrence A. Carastro Carastro ◽  
Ravi Poddar Poddar ◽  
Martin A. Brooke Brooke ◽  
Gary S. May May ◽  
...  

2012 ◽  
Vol 64 (3) ◽  
pp. 221-228 ◽  
Author(s):  
Maria Angelova ◽  
Krassimir Atanassov ◽  
Tania Pencheva

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