- author = "Daniel Howard and Simon C. Roberts",
- title = "Evolution of Mesh Refinement Rules for Impact Dynamics",
- booktitle = "Proceedings of the 2000 Congress on Evolutionary Computation CEC00",
- year = "2000",
- pages = "1297--1303",
- address = "La Jolla Marriott Hotel La Jolla, California, USA",
- publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ 08855-1331, USA",
- month = "6-9 " # jul,
- organisation = "IEEE Neural Network Council (NNC), Evolutionary Programming Society (EPS), Institution of Electrical Engineers (IEE)",
- publisher = "IEEE Press",
- keywords = "genetic algorithms, genetic programming, novel applications, impact (mechanical), evolutionary computation, learning (artificial intelligence), mechanical engineering computing, partial differential equations, mesh refinement rule evolution, impact dynamics, rule learning, adaptive mesh refinement, mesh cells, material densities, high speed impact, spherical ball, metal plate",
- ISBN = "0-7803-6375-2",
-
DOI = "
doi:10.1109/CEC.2000.870801",
- abstract = "Genetic programming (GP) was used in an experiment to investigate the possibility of learning rules that trigger adaptive mesh refinement. GP detected mesh cells that required refinement by evolving a formula involving cell quantities such as material densities. Various cell variable combinations were investigated in order to identify the optimal ones for indicating mesh refinement. The problem studied was the high speed impact of a spherical ball on a metal plate.",
-
notes = "CEC-2000 - A joint meeting of the IEEE, Evolutionary
Programming Society, Galesia, and the IEE.
IEEE Catalog Number = 00TH8512,
Library of Congress Number = 00-018644",
