A Review of Genetic Programming Application for Data Modeling
- November 29, 2019
- Posted by: RSIS
- Categories: Computer Science and Engineering, IJRSI
International Journal of Research and Scientific Innovation (IJRSI) | Volume VI, Issue XI, November 2019 | ISSN 2321–2705
A Review of Genetic Programming Application for Data Modeling
J. O. Shonubi1, D. B. Johnson2, F. E. Onuodu3
1Department of Computer Science, Federal Polytechnic Ekowe, Bayelsa State, Nigeria
2Department of Computer Science, Ignatius Ajuru University of Education, Rivers State, Nigeria
3Department of Computer Science, University of Port Harcourt, River State, Nigeria
Abstract— Genetic programming is a recent field in the family of Evolutionary Computing which is gaining wide recognition both theoretically and practically as it well suitably useable in domains that do not have clear solutions to the problems. This article reviews the use of genetic programming (GP) as an efficient tool to explore data modeling. The researchers implemented data modelling using Eureqa – a genetic programming application.
Keywords: artificial intelligence, evolutionary computing, genetic programming.
I. INTRODUCTION
There are real world problems that are encountered in human endeavour which seems or are too difficult to solve. Some of these examples include travelling salesman or knapsack problem. Some of the problem increases as the problem size increases with no known feasible exact solution methods.
Evolutionary algorithm has become a popular approach to solving these complex problems by exploiting biological evolution following Darwin theory of evolution. Evolutionary Computing (EC) mimics or simulates Darwin’s theory of biological evolution, adaptation and natural selection [1]. Evolutionary Computing forms the core standard for all evolutionary algorithm such as genetic algorithm (GA), genetic programming (GP), Evolutionary programming, evolution strategy, differential evolution as shown in fig. 1 below.
