Paper Info
Title
Developing Postfix-GP Framework for Symbolic Regression Problems
Abstract
This paper describes Postfix-GP system, postfix notation based Genetic Programming (GP), for solving symbolic regression problems. It presents an object-oriented architecture of Postfix-GP framework. It assists the user in understanding of the implementation details of various components of Postfix-GP. Postfix-GP provides graphical user interface which allows user to configure the experiment, to visualize evolved solutions, to analyze GP run, and to perform out-of-sample predictions. The use of Postfix-GP is demonstrated by solving the benchmark symbolic regression problem. Finally, features of Postfix-GP framework are compared with that of other GP systems.
Year
DOI
Venue
2015
10.1109/ACCT.2015.114
ACCT '15 Proceedings of the 2015 Fifth International Conference on Advanced Computing & Communication Technologies
Field
DocType
Volume
Object-oriented design,Architecture,Reverse Polish notation,Computer science,Genetic programming,Theoretical computer science,Graphical user interface,Artificial intelligence,Information and Communications Technology,Symbolic regression,Semantics,Machine learning
Journal
abs/1507.01687
Citations 
PageRank 
References 
0
0.34
3
Authors
2
Name
Order
Citations
PageRank
Vipul K. Dabhi1286.49
Sanjay Chaudhary222324.16