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https://hdl.handle.net/2440/75047
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Type: | Conference paper |
Title: | The experimental study of population-based parameter optimization algorithms on rule-based ecological modelling |
Author: | Cao, H. Recknagel, F. Orr, P. |
Citation: | Proceedings of the 2012 IEEE Congress on Evolutionary Computation, held in Brisbane, 10-15 June, 2012: pp.1-8 |
Publisher: | IEEE |
Publisher Place: | USA |
Issue Date: | 2012 |
Series/Report no.: | IEEE Congress on Evolutionary Computation |
ISBN: | 9781467315104 |
Conference Name: | IEEE Congress on Evolutionary Computation (2012 : Brisbane, Qld.) |
Statement of Responsibility: | Hongqing Cao, Friedrich Recknagel, Philip T. Orr |
Abstract: | This study investigates six population-based algorithms for the parameter optimization (PO) within the hybrid methodology developed for modelling algal abundance by rule-based models. These PO algorithms include: (1) Hill Climbing (2) Simulated Annealing (3) Genetic Algorithm (4) Differential Evolution (5) Covariance Matrix Adaptation Evolution Strategy and (6) Estimation of Distribution Algorithm. The effectiveness of algorithms is tested on the Cylindrospermopsis abundance data from Wivenhoe Reservoir in Queensland (Australia). We provide a systematic analysis and comparison of different parameter optimization algorithms as well as the resulting predictive rule models. |
Keywords: | ecological modelling evolutionary algorithm genetic programming parameter optimization population-based algorithm |
Rights: | U.S. Government work not protected by U.S. copyright |
DOI: | 10.1109/CEC.2012.6252957 |
Description (link): | http://www.ieee-wcci2012.org/ |
Published version: | http://dx.doi.org/10.1109/cec.2012.6252957 |
Appears in Collections: | Aurora harvest Earth and Environmental Sciences publications Environment Institute publications |
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