Created by W.Langdon from gp-bibliography.bib Revision:1.7421

- @InProceedings{Jiang:1993:afis,
- author = "Mingda Jiang and Alden H. Wright",
- title = "An adaptive function identification system",
- booktitle = "Proceedings of the IEEE/ACM Conference on Developing and Managing Intelligent System Projects, Vienna, Virginia, USA",
- year = "1993",
- pages = "47--53",
- month = mar,
- keywords = "genetic algorithms, genetic programming, Levenberg-Marquardt nonlinear regression algorithm, adaptive function identification system, adaptive system, expression-tree representation, symbolic function identification problem, adaptive systems, learning (artificial intelligence)",
- DOI = "doi:10.1109/DMISP.1993.248637",
- size = "7 pages",
- abstract = "Given data in the form of a collection of (x,y) pairs of real numbers, the symbolic function identification problem is to find a functional model of the form y=f(x) that fits the data. This paper describes an adaptive system for solution of symbolic function identification problems that combines a genetic algorithm and the Levenberg-Marquardt nonlinear regression algorithm. The genetic algorithm uses an expression-tree representation rather than the more usual binary-string representation. Experiments were run with data generated using a wide variety of function models. The system was able to find a function model that closely approximated the data with a very high success rate",
- notes = "HGSFI, Ultrix, Unidata Inc. Also known as \cite{248637}",
- }

Genetic Programming entries for Mingda Jiang Alden H Wright