- author = "O. Giustolisi and A. Doglioni and D. A. Savic and B. W. Webb",
- title = "A multi-model approach to analysis of environmental phenomena",
- journal = "Environmental Modelling \& Software",
- year = "2007",
- volume = "22",
- number = "5",
- pages = "674--682",
-
note = "The Implications of Complexity for Integrated
Resources
The Second Biannual Meeting of the International Environmental Modelling and Software Society: Complexity and Integrated Resources Management",
- keywords = "genetic algorithms, genetic programming, EPR, Evolutionary Polynomial Regression, Scientific knowledge discovery from data, Environmental modelling, Evolutionary computing, Data reconstruction",
- ISSN = "1364-8152",
-
URL = "
http://www.sciencedirect.com/science/article/pii/S1364815206000326",
-
DOI = "
doi:10.1016/j.envsoft.2005.12.026",
- size = "9 pages",
- abstract = "A data-driven methodology named Evolutionary Polynomial Regression is introduced. EPR permits the symbolic and multi-purpose modelling of physical phenomena, through the simultaneous solution of a number of models. Multi-purpose modelling or multi-modelling enables the user to make a different choice according to what the model is aiming at: (a) the scientific knowledge based on data modelling, (b) on-line and off-line forecasting, (c) data augmentation (i.e. infilling of missing data in time series) and so on. This allows a more robust model selection phase. A case study based on the application of Evolutionary Polynomial Regression to the study of the thermal behaviour of a stream is presented.",
