GP-Based Modeling Method for Time Series Prediction with Parameter Optimization and Node Alternation
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @InProceedings{yoshihara:2000:gmmtsppona,
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author = "I. Yoshihara and T. Aoyama and M. Yasunaga",
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title = "GP-Based Modeling Method for Time Series Prediction
with Parameter Optimization and Node Alternation",
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booktitle = "Proceedings of the 2000 Congress on Evolutionary
Computation CEC00",
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year = "2000",
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pages = "1475--1481",
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volume = "2",
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address = "La Jolla Marriott Hotel La Jolla, California, USA",
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publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ
08855-1331, USA",
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month = "6-9 " # jul,
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organisation = "IEEE Neural Network Council (NNC), Evolutionary
Programming Society (EPS), Institution of Electrical
Engineers (IEE)",
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publisher = "IEEE Press",
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keywords = "genetic algorithms, genetic programming, time series,
GP based model building, GP based modelling method,
backpropagation-like algorithm, complicated functions,
fast method, functional forms, model parameters,
mutation, node alternation, parameter optimisation,
seismic ground motion, time series prediction,
backpropagation, parameter estimation, statistical
analysis",
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ISBN = "0-7803-6375-2",
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DOI = "doi:10.1109/CEC.2000.870828",
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abstract = "A fast method of GP based model building for time
series prediction is proposed. The method involves two
newly-devised techniques. One is regarding
determination of model parameters: only functional
forms are inherited from their parents with genetic
programming, but model parameters are not inherited.
They are optimised by a backpropagation-like algorithm
when a child (model) is newborn. The other is regarding
mutation: nodes which require a different number of
edges, can be transformed into different types of nodes
through mutation. This operation is effective at
accelerating complicated functions e.g. seismic ground
motion. The method has been applied to a typical
benchmark of time series and many real world problems",
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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",
- }
Genetic Programming entries for
Ikuo Yoshihara
T Aoyama
M Yasunaga
Citations