Research on Software Effort Estimation Combined with Genetic Algorithm and Support Vector Regression

2011 ◽  
Author(s):  
Jin-Cherng Lin ◽  
Chu-Ting Chang ◽  
Sheng-Yu Huang
Keyword(s):  
Genetic Algorithm ◽  
Support Vector Regression ◽  
Support Vector ◽  
Effort Estimation ◽  
Software Effort Estimation

Genetic Algorithm and Support Vector Regression for Software Effort Estimation

2011 ◽  
Vol 282-283 ◽  
pp. 748-752 ◽  
Author(s):  
Jin Cherng Lin ◽  
Chu Ting Chang
Keyword(s):  
Genetic Algorithm ◽  
Support Vector ◽  
Effort Estimation ◽  
Software Effort Estimation ◽  
Software Developers ◽  
Factors Affecting ◽  
Proposed Model ◽  
Vector Machines ◽  
Best Parameter ◽  
The Cost

For software developers, accurately forecasting software effort is very important. In the field of software engineering, it is also a very challenging topic. Miscalculated software effort in the early phase might cause a serious consequence. It not only effects the schedule, but also increases the cost price. It might cause a huge deficit. Because all of the different software development team has it is own way to calculate the software effort, the factors affecting project development are also varies. In order to solve these problems, this paper proposes a model which combines genetic algorithm (GA) with support vector machines (SVM). We can find the best parameter of SVM regression by the proposed model, and make more accurate prediction. During the research, we test and verify our model by using the historical data in COCOMO. We will show the results by prediction level (PRED) and mean magnitude of relative error (MMRE).

scholarly journals Applying hybrid support vector regression and genetic algorithm to water alternating CO 2 gas EOR

2020 ◽  
Vol 10 (3) ◽  
pp. 613-630 ◽  
Author(s):  
Menad Nait Amar ◽  
Noureddine Zeraibi ◽  
Ashkan Jahanbani Ghahfarokhi
Keyword(s):  
Genetic Algorithm ◽  
Support Vector Regression ◽  
Support Vector
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