[1] Evolutionary Modeling of Complex Systems Based on
Genetic Programming.
Hongqing Cao
PhD thesis. Wuhan University, China,
June, 1999 (in Chinese). Supervisor: Professor Lishan
Kang.
[Abstract]
[2] The Study of Some Algorithms and Diagnosability
in Probabilisitic Diagnosis and Distributed Diagnosis
by Computer Simulations.
Hongqing Cao
Master's thesis, Chongqing University,
China, June,
1996 (in Chinese). Supervisor: Tinghuai Chen.
Journal Papers
[1] Generic limnological models on the touchstone: Testing the lake simulation library SALMO-OO and the rule-based microcystis agent for warm-monomictic hypertrophic lakes in South Africa.
Friedrich Recknagel, C. van Ginkel, Hongqing Cao, Lydia Cetin and Byron Zhang.
Ecological Modelling, 215: 144-158, 2008.
[2] Generic limnological models on the touchstone: Testing the lake simulation library SALMO-OO and the rule-based microcystis agent for warm-monomictic hypertrophic lakes in South Africa.
Recknagel, F., Cao, H., van Ginkel, C., van der Molen, D., Park, H. and N. Takamura.
Verh. Internat. Verein. Limnol. 30(2): 191-197, 2008.
[3] Process-based simulation
library SALMO-OO for lake ecosystems. Part 2: Multi-objective parameter
optimization by evolutionary algorithms.
Hongqing Cao, Friedrich Recknagel,
Lydia Cetin, Byron Zhang
Ecological Informatics, 3: 181-190, 2008.
[PDF (1476 K)]
[4] Rule-based agents for forecasting algal population dynanics in freshwater lakes discovered by hybrid
evolutionary algorithms.
Amber Welk, Friedrich Recknagel,
Hongqing Cao, Wai-Sun Chan,
Anita Talib
Ecological Informatics, 3: 46-54, 2008.
[PDF (1340 K)]
[5] Predictive function and rules for population dynamics of Microcystis aeruginosa in the
regulated Nakdong
River (South Korea) discovered by
evolutionary algorithms.
Dong-Kyun Kim, Hongqing Cao,
Kwang-seuk Jeong, Friedrich
Recknagel, Gea-Jae Joo
Ecological Modelling, 203: 147-156, 2007.
[PDF (987 K)]
[DOI]
[6] Elucidation and short-term forecasting of Microcystin
concentrations in Lake Suwa (Japan) by means
of artificial neural networks and evolutionary algorithms.
Wai Sum Chan, Friedrich Recknagel,
Hongqing Cao, Ho-Dong Park
Water Research, 41: 2247-2255, 2007.
[PDF (952 K)]
[DOI]
[7] A new tree structure coding for equivalent circuit and evolutionary
estimation of parameters.
Jingxian Yu, Hongqing Cao,
Yanbin He
Chemometrics and Intelligent Laboratory
Systems, 85(1): 27-39, 2007.
[PDF (401 K)]
[DOI]
[8] Forecasting of dinoflagellate blooms in
warm-monomictic hypertrophic reservoirs in South Africa by
means of rule-based agents.
Van Ginkel C, Cao H,
Recknagel F, Du Plessis S
Water SA. Vol. 33, No. 4, pp. 531-538, 2007.
[PDF (867 K)]
[9] Anthropometrical Characteristics among professional baseball
pitchers: A hybrid evolutionary algorithm approach.
L. Valandro, L. Colombo, H. Cao, F. Recknagel, S. Dun, EL. SEcco
International Journal of Computer Science in Sport. Vol. 6, No. 1, pp.
34-46, 2007.
[PDF (268 K)]
[10] Unravelling and forecasting algal
population dynamics in two lakes different in morphometry
and eutrophication by neural and evolutionary computation.
Friedrich Recknagel, Hongqing Cao,
Bomchul Kim, Noriko Takamura,
Amber Welk
Ecological Informatics, 1(2):133-151, 2006.
[PDF (2834 K)]
[DOI]
[11] Discovery of predictive rule sets for chlorophyll-a dynamics in the Nakdong River (Korea) by means of the hybrid
evolutionary algorithm HEA.
Hongqing Cao, Friedrich Recknagel,
Gea-Jae Joo, Dong-Kyun Kim
Ecological Informatics, 1(1):43-53, 2006.
[PDF (457 K)]
[DOI]
[12] The dynamic evolutionary modeling of HODEs
for time series prediction.
Hongqing Cao, Lishan Kang, Yuping Chen, Tao Guo
Computers & Mathematics with Applications, 46(8-9):1397-1411, 2003.
[PDF
(1040 K)]
[DOI]
[13] An experimantal study of some control
parameters in parallel genetic programming.
Hongqing Cao, Jingxian Yu, Lishan Kang, R I Bob Mckay
Neural, Parallel and Scientific Computation, 11(4):377-393, 2003.
[PDF (104 K)]
[14] Evolutionary modeling and prediction for discharge lifetime of
battery systems.
Hongqing Cao, Jingxian Yu, Lishan Kang, Hanxi Yang, Xinping Ai
Computers & Chemistry, 25(3): 251-259, 2001.
[PDF (300 K)]
[DOI]
[15] Evolutionary modeling of systems of ordinary differential equations
with genetic programming.
Hongqing Cao, Lishan Kang, Yuping Chen, Jingxian Yu
Genetic Programming & Evolvable Machines (invited paper),
1(4):309-337, 2000.
[PDF (235K)]
[DOI]
[16] A two-level hybrid evolutionary algorithm for modeling
one-dimensional dynamic system by higher-order ODE models.
Hongqing Cao, Lishan Kang, Guo Tao,Yuping Chen, Hugo de Garis
IEEE Transactions on Systems, Man and Cybernetics Part B: Cybernetics,
30(2):351-357, 2000.
[PDF (193 K)]
[17] The kinetic evolutionary modeling of complex systems of chemical
reactions.
Hongqing Cao, Jingxian Yu, Lishan Kang, Yuping Chen, Yongyan Chen
Computers & Chemistry, 23(2):143-151,1999.
[PDF (223 K)]
[DOI]
[18] A new approach to estimation of the electrocrystallization
parameters.
Jingxian Yu, Hongqing Cao,
Yongyan Chen, Lishan Kang, Hanxi Yang
Journal of Electroanalytical Chemistry,
474(1):69-73, 1999.
[PDF (125 K)]
[19] A hybrid evolutionary modeling algorithm for system of ordinary
differential equations.
Hongqing Cao, Lishan Kang, Zbigniew Michalewicz, Yuping Chen
Neural, Parallel & Scientific Computations, 6(2):171-188,1998.
[Abstract]
Conference Papers
[1] A multiscale modeling framework based on P
systems.
Francisco J. Romero-Campero, Jamie Twycross, Hongqing Cao, Jonathan Blakes,
and Natalio Krasnogor
In: David Wolfe Corne,
Pierluigi Frisco, Gheorghe Paunm,
Grzegorz Rozenberg, and Arto Salomaa (Eds.), Lecture
Notes in Computer Science, LNCS5391, 9th International Workshop on
Membrane Computing, WMC 2008, Edinburgh,
UK, July 2008, pp. 63-77, 2008.
[PDF (414 K)]
[2] Structure and parameter estimation for cell systems biology models. (Best Paper Award)
Francisco J. Romero-Campero, Hongqing Cao,
Miguel Camara, Natalio Krasnogor
In the proceedings of 2008 Genetic and Evolutionary Computation Conference
(GECCO-2008 )(CD), July 12-16, 2008, Atlanta,
USA. pp.331-338.
[PDF (6.39 M)]
[3] Enbodiment of the process-based simulation
library SALMO-OO for lake ecosystems by evolutionary algorithms.
Hongqing Cao, Friedrich Recknagel, Lydia
Cetin, Byron Zhang
Presented in: the 5th International Conference on Ecological Informatics
(ISEI5), December 4-7, 2006, Santa
Barbara, CA, USA.
[4] Rule-based agents for forecasting algal biomass and species dynamics
in freshwater lakes discovered by hybrid evolutionary algorithms.
Amber Welk, Hongqing Cao,
Wai Sum Chan, Friedrich Recknagel
Present in the 5th International Conference on Ecological Informatics
(ISEI5), December 4-7, 2006, Santa Barbara, CA, USA.
[5] Use of recurrent ANN and hybrid EA for the prediction of
phytoplankton abundance and succession before and after eutrophication
control of two shallow lakes.
A. Talib, F. Recknagel, H.
Cao, D.T. van der Molen
In Andre Zerger & Robert M. Argent (eds.). MODSIM05:
the Proceedings of the International Congress on Modelling
and Simulation (Abstracts), December 12-15, 2005, Melbourne, Australia.
pp.13.
[PDF (974 K)]
[6] Rule set discovery for prediction and explanation of chlorophyll-a
dynamics in the Nakdong
River (Korea) by using a two-level hybrid
evolutionary algorithm.
Hongqing Cao, Friedrich Recknagel,
Dong-Kyun Kim
Presented in: the 4th Conference of the International Society for Ecological
Informatics (ISEI4), Busan (Pusan),
Korea,
October 24-28, 2004.
[7] Predictive function and rules for population dynamics of microcystis aeruginosa in the
regulated river, Nakdong (South Korea), discovered by
evolutionary algorithms.
Dong-Kyun Kim, Hongqing Cao,
Friedrich Recknagel, Gea-Jae
Joo
Presented in: the 4th Conference of the International Society for Ecological
Informatics (ISEI4), Busan (Pusan),
Korea,
October 24-28, 2004.
[8] An evolutionary approach for modeling the equivalent circuit for
electrochemical impedance spectroscopy.
Hongqing Cao, Jingxian Yu, Lishan Kang
In: the Proceedings of the 2003 Congress on Evolutionary Computation
(CEC2003). December 9-12, 2003. Canberra,
Australia. IEEE
Press. Vol. 3, pp. 1819-1825, 2003.
[PDF (432 K)]
[9] Evolutionary modeling of ordinary differential equations for dynamic
systems.
Hongqing Cao, Lishan Kang, Yuping Chen
In W. Banzhaf, J. Daida, A.
E. Eiben, M. H. Garzon, V. Honavar, M. Jakiela, and R. E.
Smith (eds.). GECCO-99: Proceedings of the Genetic and Evolutionary
Computation Conference, July 13-17, 1999, Orlando, Florida, USA. Vol. 2, pp. 959-965, Morgan
Kaufmann Publishers.
[PDF (87 K)]
[10] The dynamic evolutionary modeling of higher-order ordinary
differential equations for time series real-time prediction.
Lishan Kang, Hongqing Cao,
Yuping Chen
In: Proceedings of the 1999 Congress on Evolutionary Computation, July 6-9,
1999. Washington D. C., USA, Vol. II, 1224-1229, IEEE Service
Center.
[11] A two-level evolutionary algorithm for modeling system of ordinary
differential equations.
Hongqing Cao, Lishan Kang, Zbigniew Michalewicz, Yuping Chen
In Genetic Programming 1998: Proceedings of the Third Annual Conference,
David E., Iba, Hitoshi, and Riolo,
Rick L. (editors), July 22-25, 1998, University of Wisconsin, Madison,
Wisconsin. San Francisco, CA: Morgan Kaufmann. pp.17-22.
Posters
[1] An integrated
development environment for synthetic biology models.
Jonathan Blakes, Francisco J.
Romero-Campero, Jamie Twycross,
Hongqing Cao, and Natalio Krasnogor.
Poster
presented at European Conference on
Synthetic Biology (ECSB) II: Design,
Programming and Optimization of Biological Systems, 29 March-03 April,
2009, Sant Feliu de Guixols, Spain.
[PDF (1931K)]
[2] A modular and stochastic approach to the study of gene circuits using
P systems.
Francisco J. Romero-Campero, Jonathan Blakes, Hongqing Cao, Miguel Camara, and
Natalio Krasnogor
Poster presented at Genomes to
Systems 2008 March 17-19, Manchester,
UK.
[PDF (583K)]
Book Chapters
[1] Hybridisation of process-based ecosystem models with evolutionary algorithms: Multi-objective optimisation of process representations and parameters of the lake simulation library SALMO-OO.
Hongqing Cao and Friedrich Recknagel.
In Jorgensen, S.E., Chon, T.S. and F. Recknagel (editors), Handbook of Ecological Modelling and Informatics, Chapter 10, pp. 169-185. WIT Press, Southampton, 2009.
[PDF (1240 K)]
[2] Ecological informatics by means of neural, evolutionary and object-oriented computation.
Friedrich Recknagel and Hongqing Cao.
In Jorgensen, S.E., Chon, T.S. and F. Recknagel (editors), Handbook of Ecological Modelling and Informatics, Chapter 9, pp. 141-168, WIT Press, Southampton, 2009.
[3] Hybrid evolutionary algorithm
for rule set discovery in time-series data to forecast and explain algal
population dynamics in two lakes different in morphometry
and eutrophication.
H. Cao, F. Recknagel,
B. Kim, N. Takamura
In Friedrich Recknagel, editor, Ecological
Informatics. 2nd Edition, Chapter 17, pp. 347-367. Springer-Verlag Berlin, 2006.
[PDF (531 K)]
[4] Chinese version of
“How to Solve it: Modern Heuristics”.
written
by Z.Michalewicz and D. B. Fogel,
translated into Chinese by Hongqing Cao, Yan
Li, Hongbing Dong and Zhijian
Wu. Beijing: Power Press of China, 2003.
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