%0 Conference Paper %1 Lopez:2002:WSC %A Lopez, Antonio M. %A Lopez, Hilario %A Sanchez, Luciano %B Advances in Soft Computing - Engineering, Design and Manufacturing %C London %D 2003 %E Benitez, Jose %E Cordon, Oscar %E Hoffmann, Frank %E Roy, Rajkumar %I Springer %K GA-P Hierarchical Identification, System algorithms, genetic models programming, %P 371--380 %T GA-P based search of structures and parameters of dynamical process models %U http://www.di.uniovi.es/~luciano/articulos/alopez_wsc7.pdf %X The most effective approaches for evolutionary identifying dynamical processes depend on iterative trial-error searches in a hierarchical fashion: a new structure is proposed first; then, its set of parameters is numerically determined, and the process is repeated until a model accurate enough is found. Canonical Genetic Programming has been used to automate this search; but its output can be diffcult to interpret. Because of this reason, the use of hierarchical learning methods, that combine GP search of structures with deterministic optimisation algorithms, has been proposed. We will show in this paper that the output of such methods can be further improved with non hierarchical algorithms. In particular, we will show that the use of GA-P improves the interpretability of the models and does a better model search than previous approaches.

@inproceedings{Lopez:2002:WSC, abstract = {The most effective approaches for evolutionary identifying dynamical processes depend on iterative trial-error searches in a hierarchical fashion: a new structure is proposed first; then, its set of parameters is numerically determined, and the process is repeated until a model accurate enough is found. Canonical Genetic Programming has been used to automate this search; but its output can be diffcult to interpret. Because of this reason, the use of hierarchical learning methods, that combine GP search of structures with deterministic optimisation algorithms, has been proposed. We will show in this paper that the output of such methods can be further improved with non hierarchical algorithms. In particular, we will show that the use of GA-P improves the interpretability of the models and does a better model search than previous approaches.}, added-at = {2008-06-19T17:35:00.000+0200}, address = {London}, author = {Lopez, Antonio M. and Lopez, Hilario and Sanchez, Luciano}, biburl = {https://www.bibsonomy.org/bibtex/2c2fad5014c3f22fdeca1487a602dc7ed/brazovayeye}, booktitle = {Advances in Soft Computing - Engineering, Design and Manufacturing}, editor = {Benitez, Jose and Cordon, Oscar and Hoffmann, Frank and Roy, Rajkumar}, interhash = {5487a9df55fdd92b88eff1f7047c3465}, intrahash = {c2fad5014c3f22fdeca1487a602dc7ed}, keywords = {GA-P Hierarchical Identification, System algorithms, genetic models programming,}, month = {September 23 - October 4}, note = {on line}, notes = {WSC7 http://wsc7.ugr.es Workshop in 2002 but published by Springer in October 2003. Fig. 2. SMOG evolution. Canonical GP is used for structural search and Hooke-Jeeves method is used for parameter tuning. Modeling direct electrical current motor.}, pages = {371--380}, publisher = {Springer}, size = {10 pages}, timestamp = {2008-06-19T17:45:50.000+0200}, title = {{GA}-{P} based search of structures and parameters of dynamical process models}, url = {http://www.di.uniovi.es/~luciano/articulos/alopez_wsc7.pdf}, year = 2003 }