Predicting and managing reservoir total phosphorus by using modified grammatical evolution coupled with a macro-genetic algorithm

Environmental Modelling and Software

Volumn 38, Issue , 2012, Pages 89-100

  Chen, Li ^a   Kao, Shuh Ji ^b,c   Traore, Seydou ^d  

^a CHUNG HUA UNIVERSITY   (Taiwan)

^b RESEARCH CENTER FOR ENVIRONMENTAL CHANGES   (Taiwan)

^c XIAMEN UNIVERSITY   (China)

^d NATIONAL PINGTUNG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Taiwan)

Author keywords

Back propagation neural network (BPNN); Grammatical evolution (GE); Macro evolutionary genetic algorithm (MEGA); Total phosphorous (TP); Water quality

Indexed keywords

BACK-PROPAGATION NEURAL NETWORKS; CHEMICAL LOAD; FORCING FUNCTION; GENETIC DIVERSITY; GRAMMATICAL EVOLUTION; INPUT VARIABLES; LOCAL OPTIMA; MACRO-EVOLUTIONARY GENETIC ALGORITHM (MEGA); MATHEMATICAL EQUATIONS; MULTILINEAR REGRESSION; OPTIMAL SOLUTIONS; PHYSICAL MODEL; PREDICTIVE CAPABILITIES; PROGRAMMING SYSTEM; QUALITY REQUIREMENTS; REDUCTION RATE; SEARCHING EFFICIENCY; SUBTROPICAL DEEP RESERVOIRS; TOTAL PHOSPHOROUS; TOTAL PHOSPHORUS;

COMPUTATIONAL GRAMMARS; EUTROPHICATION; MODELS; NEURAL NETWORKS; NONLINEAR EQUATIONS; OPTIMIZATION; PHOSPHORUS; PRECIPITATION (CHEMICAL); TORSIONAL STRESS; WATER QUALITY;

GENETIC ALGORITHMS;

ARTIFICIAL NEURAL NETWORK; COMPLEXITY; EUTROPHICATION; GENETIC ALGORITHM; HYDROLOGICAL MODELING; NUMERICAL MODEL; OPTIMIZATION; PHOSPHORUS; PREDICTION; RESERVOIR; SENSITIVITY ANALYSIS; WATER QUALITY;

EID: 84861962150     PISSN: 13648152     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.envsoft.2012.05.006     Document Type: Article

References (34)

1. Carpenter J.H., Pritchard D.W., Whaley R.C. Observations of eutrophication and nutrient cycles in some coastal plain estuaries. Eutrophication: Causes, Consequences, Correctives 1969, 210-221. Natl. Acad. Sci., Washington, DC.
2. Chang F.J., Chen L. Real-coded genetic algorithm for rule-based flood control reservoir management. Water Resource Management 1998, 12:185-198.
3. Chang F.J., Chen L., Chang L.C. Optimizing the reservoir operation rule curves by genetic algorithms. Hydrological Processes 2005, 18:2277-2289.
4. Chen L., Chang F.J. Applying real-coded multi-population genetic algorithm to multi-reservoir operation. Hydrological Processes 2007, 21:688-698.
5. Chen L., Wang T.-S. Modeling strength of high-performance concrete using an improved grammatical evolution combined with macrogenetic algorithm. Journal of Computing in Civil Engineering, ASCE 2010, 24:281-288.
6. Chen L., McPhee J., Yeh W.-G. A diversified multiobjective GA for optimizing reservoir rule curves. Advances in Water Resources 2007, 30:1082-1093.
7. Chen L., Tan C.-H., Kao S.-J., Wang T.-S. Improvement of remote monitoring on water quality in a subtropical reservoir by incorporating grammatical evolution with parallel genetic algorithms into satellite imagery. Water Research 2008, 42(1-2):296-306.
8. Chen L., Yeh K.-C., Wei H.-P., Liu G.-R. Estimating Typhoon rainfall over ocean from SSM/I satellite data using an improved genetic programming. Hydrological Processes 2011, 25:2573-2583.
9. Chen L. Real-coded genetic algorithm optimization of long-term reservoir operation. Journal of the American Water Resources Association 2003 a, 39(5):1157-1165.
10. Chen L. A study of applying macro-evolutionary genetic programming to concrete strength estimation. Journal of Computing in Civil Engineering. ASCE 2003 b, 17(4):290-294.
11. Chen L. Macro-grammatical evolution for nonlinear time series modeling - A case study of reservoir inflow forecasting. Engineering with Computers 2011, 10.1007/s00366-011-0212-3.
12. Diamantopoulou M.J. Filling gaps in diameter measurements on standing tree boles in the urban forest of Thessaloniki, Greece. Environmental Modelling & Software 2010, 25:1857-1865.
13. Diogo P.A., Fonseca M., Coelho P.S., Mateus N.S., Almeida M.C., Rodrigues A.C. Reservoir phosphorous sources evaluation and water quality modeling in a transboundary watershed. Desalination 2008, 226:200-214.
14. Elseth G.D., Baumgardner K.D. Principles of Modern Genetics 1995, West, St. Paul MN.
15. Friedel M.J. A data-driven approach for modeling post-fire debris-flow volumes and their uncertainty. Environmental Modelling & Software 2011, 26:1583-1598.
16. Garnier J., Nemery J., Billen G., Thery S. Nutrient dynamics and control of eutrophication in the Marne River system: modelling the role of exchangeable phosphorus. Journal of Hydrology 2005, 304:397-412.
17. Hashmi M.Z., Shamseldin A.Y., Melville B.W. Statistical downscaling of watershed precipitation using Gene Expression Programming (GEP). Environmental Modelling & Software 2011, 26:1639-1646.
18. Huang J.C., Lee T.Y., Kao S.J., Hsu S.C., Lin H.J., Peng T.R. The nitrate export in subtropical mountainous catchment: implication for land use change impact. Hydrology and Earth System Sciences Discussions 2010, 7:9293-9326.
19. Kao S.J., Shiah F.K., Owen J. Export of dissolved inorganic nitrogen in a partially cultivated mountainous watershed in Taiwan. Water, Air and Soil Pollution 2004, 156(1-4):211-228.
20. Kisi O., Haktanir T., Ardiclioglu M., Ozturk O., Yalcin E., Uludag S. Adaptive neuro-fuzzy computing technique for suspended sediment estimation. Advances in Engineering Software 2009, 40:438-444.
21. Kralisch S., Fink M., Flügel W.A., Beckstein C. A neural network approach for the optimization of watershed management. Environmental Modelling and Software 2003, 18(8-9):815-823.
22. Kuo J.T., Wang Y.Y., Lung W.S. A hybrid neural-genetic algorithm for reservoir water quality management. Water Research 2006, 40:1367-1376.
23. Kuo J.T., Hsieh M.H., Lung W.S., She N. Using artificial neural network for reservoir eutrophication prediction. Ecological Modeling 2007, 200:171-177.
24. Kushchu I. Genetic programming and evolutionary generalization. IEEE Transactions on Evolutionary Computation 2002, 6(5):431-442.
25. Lee, Joseph H.W., Huang Y., Dickman M., Jayawardena A.W. Neural network modelling of coastal algal blooms. Ecological Modeling 2003, 159:179-210.
26. Nutrients and Eutrophication. Spec. Symp. Am. Soc. Limnol. Oceanogr 1972, vol. 1. Allen Press, Lawrence, KS. G.E. Likens (Ed.).
27. Maier H.R., Morgan N., Chow C.W.K. Use of artificial neuralnetworks for predicting optimal alum doses and treated water quality parameters. Environmental Modelling and Software 2004, 19(5):485-494.
28. Maier H.R., Jain A., Dandy G.C., Sudheer K.P. Methods used for the development of neural networks for the prediction of water resource variables in river systems: current status and future directions. Environmental Modelling & Software 2010, 25:891-909.
29. Marin J., Sole R. Macroevolutionary algorithms: a new optimization method on fitness landscapes. IEEE Transactions on Evolutionary Computation 1999, 3(4):272-285.
30. Mau D.P., Christensen V.G. Comparison of Sediment Deposition in Reservoirs of Four Kansas Watersheds 2000, U.S. Geological Survey, Fact Sheet, 102-00, 4 p.
31. May R.J., Dandy G.C., Maier H.R., Nixon J.B. Application of partial mutual information variable selection to ANN forecasting of water quality in water distribution systems. Environmental Modelling & Software 2008, 23:1289-1299.
32. Naur P. Revised report on the Algorithmic Language ALGOL 60. Communication of the ACM 1963, 6(1):1-17.
33. Raymont J.E.G. Plankton and productivity in the oceans. Phytoplankton 1980, 489.
34. Zou R., Lung W.S., Guo H. Neural network embedded MonteCarlo approach for water quality modelling under input information uncertainty. Journal of Computing in Civil Engineering. ASCE 2002, 16(2):135-142.