Signal path oriented approach for generation of dynamic process models
作者： Peter Marenbach , Kurt D. Bettenhausen , Stephan Freyer
DOI:
关键词:
摘要: The article at hand discusses a tool for automatic generation of structured models complex dynamic processes by means genetic programming. In contrast to other techniques which use programming find an appropriate arithmetic expression in order describe the input-output behaviour process, this is based on block oriented approach with transparent description signal paths. A short survey computer system identification given and basic concept SMOG (Structured MOdel Generator) described. Furthermore latest extensions are presented detail, including automatically defined sub-models qualitative fitness criteria.
tu-darmstadt.de参考文章(17)
Peter J. Angeline, Genetic programming and emergent intelligence Advances in genetic programming. pp. 75- 97 ,(1994)
Hartmut Pohlheim, Peter Marenbach, Generation of structured process models using genetic algorithms Springer-Verlag. ,(1996)
Wolfgang Banzhaf, Peter Nordin, Complexity Compression and Evolution international conference on genetic algorithms. pp. 310- 317 ,(1995)
John R. Koza, Genetic Programming II: Automatic Discovery of Reusable Programs ,(1994)
Rolf Isermann, Digital Control Systems ,(1981)
Hartmut Pohlheim, Peter Marenbach, Generation of Structured Process Models Using Genetic Programming artificial intelligence and the simulation of behaviour. pp. 102- 109 ,(1996) , 10.1007/BFB0032776
John R. Koza, Genetic Programming: On the Programming of Computers by Means of Natural Selection ,(1992)
Peter J. Fleming, Carlos M. Fonseca, Genetic Algorithms for Multiobjective Optimization: FormulationDiscussion and Generalization international conference on genetic algorithms. pp. 416- 423 ,(1993)
Hitoshi Iba, Hugo de Garis, Takio Kurita, Taisuke Sato, System Identification using Structured Genetic Algorithms international conference on genetic algorithms. pp. 279- 286 ,(1993)
Hitoshi Iba, Hugo de Garis, Taisuke Sato, Temporal Data Processing Using Genetic Programming international conference on genetic algorithms. pp. 279- 286 ,(1995)