- author = "Hitoshi Iba",
- title = "Inference of differential equation models by genetic programming",
- journal = "Information Sciences",
- year = "2008",
- volume = "178",
- number = "23",
- pages = "4453--4468",
- month = "1 " # dec,
- note = "Special Section: Genetic and Evolutionary Computing",
- keywords = "genetic algorithms, genetic programming, Ordinary differential equations, Genome informatics",
- ISSN = "0020-0255",
-
DOI = "
doi:10.1016/j.ins.2008.07.029",
- size = "16 pages",
- abstract = "This paper describes an evolutionary method for identifying a causal model from the observed time-series data. We use a system of ordinary differential equations (ODEs) as the causal model. This approach is known to be useful for practical applications, e.g., bioinformatics, chemical reaction models, control theory, etc. To explore the search space more effectively in the course of evolution, the right-hand sides of ODEs are inferred by genetic programming (GP) and the least mean square (LMS) method is used along with the ordinary GP. We apply our method to several target tasks and empirically show how successfully GP infers the systems of ODEs. We also describe an extension of the approach to the inference of differential equation systems with transcendental functions.",
-
notes = "The reaction between formaldehyde and carbamide in the
aqueous solution gives methylol urea which continues to
react with carbamide and form methylene urea. GP with
LMS. Forced vibration with damping. ODE. Penalty
against bloat. S-expression: power-law exponents for
terminal set. MDL. Fourth order Runge-Kutta. Numerical
overflow -> poor fitness -> weeded out.
Synthetic data.
E-CELL SE, Michaelis-Menten law.
Levenberg-Marquardt Is genotype {"}repaired{"} or just phenotype? p4467 considers possibility that there is more than one solution.",
