An Automatic Learning System to Derive Multipole and Local Expansions for the Fast Multipole Method
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- @InProceedings{Razavi:2012:ICSI,
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author = "Seyed Naser Razavi and Nicolas Gaud and
Abderrafiaa Koukam and Nasser Mozayani",
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title = "An Automatic Learning System to Derive Multipole and
Local Expansions for the Fast Multipole Method",
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booktitle = "Third International Conference on Swarm Intelligence
(ICSI)",
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year = "2012",
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editor = "Ying Tan and Yuhui Shi and Zhen Ji",
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volume = "7332",
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series = "Lecture Notes in Computer Science",
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pages = "1--10",
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address = "Shenzhen, China",
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month = jun,
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming, agent-based
simulation, complex systems, fast Multipole Method",
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isbn13 = "978-3-642-31019-5",
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DOI = "doi:10.1007/978-3-642-31020-1_1",
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size = "10 pages",
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abstract = "This paper introduces an automatic learning method
based on genetic programming to derive local and
multipole expansions required by the Fast Multipole
Method (FMM). FMM is a well-known approximation method
widely used in the field of computational physics,
which was first developed to approximately evaluate the
product of particular N by N dense matrices with a
vector in O(N log N) operations. Later, it was applied
successfully in many scientific fields such as
simulation of physical systems, Computer Graphics and
Molecular dynamics. However, FMM relies on the
analytical expansions of the underlying kernel function
defining the interactions between particles, which are
not always obvious to derive. This is a major factor
limiting the application of the FMM to many interesting
problems. Thus, the proposed method here can be
regarded as a useful tool helping practitioners to
apply FMM to their own problems such as agent-based
simulation of large complex systems. The preliminary
results of the implemented system are very promising,
and so we hope that the proposed method can be applied
to other problems in different application domains.",
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notes = "See \cite{Razavi:2012:AIc} Also known as
\cite{RazaviGaudKoukamMozayani2012_367}",
- }
Genetic Programming entries for
Seyed Naser Razavi
Nicolas Gaud
Abderrafiaa Koukam
Nasser Mozayani
Citations