- author = "Miran Brezocnik and Miha Kovacic and Leo Gusel",
- title = "Comparison Between Genetic Algorithm and Genetic Programming Approach for Modeling the Stress Distribution",
- journal = "Materials and Manufacturing Processes",
- year = "2005",
- volume = "20",
- number = "3",
- pages = "497--508",
- month = may,
- keywords = "genetic algorithms, genetic programming, Metal forming, Stress distribution, System modelling",
- ISSN = "1042-6914",
-
URL = "
http://journalsonline.tandf.co.uk/openurl.asp?genre=article&issn=1042-6914&volume=20&issue=3&spage=497",
-
DOI = "
doi:10.1081/AMP-200053541",
- abstract = "We compare genetic algorithm (GA) and genetic programming (GP) for system modelling in metal forming. As an example, the radial stress distribution in a cold-formed specimen (steel X6Cr13) was predicted by GA and GP. First, cylindrical workpieces were forward extruded and analysed by the visioplasticity method. After each extrusion, the values of independent variables (radial position of measured stress node, axial position of measured stress node, and coefficient of friction) were collected. These variables influence the value of the dependent variable, radial stress. On the basis of training data, different prediction models for radial stress distribution were developed independently by GA and GP. The obtained models were tested with the testing data. The research has shown that both approaches are suitable for system modeling. However, if the relations between input and output variables are complex, the models developed by the GP approach are much more accurate.",
-
notes = "A1 Laboratory for Intelligent Manufacturing Systems,
University of Maribor, Faculty of Mechanical
Engineering, Maribor, Slovenia
A2 Laboratory for Material Forming, University of Maribor, Faculty of Mechanical Engineering, Maribor, Slovenia",
