------------- NOTE: There's one relevant piece of publication missing, which is the Ph.D. thesis of M. Baptist, one of the co-authors of our work. As the thing is 12 MB large, and only a certain part of the work is relevant to the application, I thought it best not to send it to you in this email. It can be found however through http://www.library.tudelft.nl/dissertations/2940/f_203505_true_EN.html And in principle it's okay that it's mirrored for the competition. Note however that only chapter 4 is relevant for the application. ------------- (1) Determining Equations for Vegetation Induced Resistance using Genetic Programming Modelling Floodplain Biogeomorphology (Chapter 4) (2) Maarten Keijzer, mkeijzer@xs4all.nl Martin Baptist, M.J.Baptist@citg.tudelft.nl Vladan Babovic, babovic@wldelft.nl Javier Uthurburu, j.uthurburu@hotmail.com For Keijzer, Babovic & Uthurburu WL | Delft Hydraulics Rotterdamseweg 185 P.O. Box 177 2600 MH Delft The Netherlands For Baptist: M.J. Baptist Delft University of Technology Faculty of Civil Engineering and Geosciences Hydrology section Stevinweg 1 2628 CN Delft the Netherlands (3) Maarten Keijzer (4) Determining Equations for Vegetation Induced Resistance using Genetic Programming: Inducing equations based on theory and data is a time-honoured technique in science. This is usually done manually, based on theoretical understanding and previously established equations. In this work, for a particular problem in hydraulics, human induction of equations is compared with the use of genetic programming. It will be shown that even with the use of synthetic data for training, genetic programming was capable of identifying a relationship that was more concise and more accurate than the relationship uncovered by scientists. As such this is a human-competitive result. Furthermore it will be shown that the genetic programming induced expression could be embedded in a line of theoretical work, filling in a few gaps in an already established line of reasoning. The resulting equation is the most accurate and elegant formulation of vegetation induced resistance to date. Modelling Floodplain Biogeomorphology: Understanding the interactions between the ecosystem and the morphology of river floodplains, i.e. floodplain biogeomorphology, is becoming increasingly important in view of modern river management and climate change. There is a need for predictive models for the natural response of river floodplains to hydraulic measures and river rehabilitation, such as river widening, construction of secondary channels and floodplain lowering. This thesis investigates floodplain biogeomorphology from a modeller's perspective. It addresses management concepts such as room-for-the-river and cyclic floodplain rejuvenation, in which a symbiosis is sought for between flood management and nature rehabilitation, and it shows how 1-D, 2-D and 3-D numerical models can be used to support them. Its main focus is on one of the knowledge gaps emerging from these model applications, viz. the effect of floodplain vegetation on the bed shear stress and subsequent bedload sediment transport. By means of a combination of theory development, flume experiments and field work, this research has resulted into a number of practically applicable and validated formulations for the hydraulic resistance and bed shear stress reduction of vegetation. These can be applied in large-scale numerical morphodynamic models to better design river measures in combination with nature rehabilitation. (5) B, D, E, F, G (6) The equation found by Genetic Programming for resistance induced vegetation is ultimately a refinement of the formula proposed by Antoine Chezy in 1776. Over the years the problem for non-vegetated streams has been satisfactory solved, for streams containing vegetation however, the formulation of resistance (roughness) was still largely unsolved. In a recent literature survey, more than 800 papers have been published in the last two decades on the subject of vegetation roughness alone (G). These papers present experimental results and equations aimed to fit the experiment results. Many of these equations are attempts at curve-fitting, and don't have a solid theoretical backing. Both the GECCO paper and the Ph.D. thesis named here present two equations that have been build by one of the co-authors in order to create a physically sound equation for resistance induced vegetation based on first principles. Alongside it, GP was used to create an expression based on data generated by a significantly more complex dynamical model. Compared with the expressions based on first principles, which are state of the art in the field, the GP induced expression was (a) more accurate, (b) amenable to analysis and (c) significantly more simple. Comparing the GP equation with the equations in the literature corroborates this. The GP induced equation is the most accurate equation for resistance induced vegetation over a wide range of conditions (B,E). This was tested using experimental results from 17 different studies. The work of Kouwen is particularly relevant for appreciating the GP induced expression. In 1969 Kouwen proposed a skeleton expression for vegetation induced resistance in which two key components are still missing. This skeleton is theoretically sound. The GP induced formulation is an instantiation of Kouwen's framework, with two concrete expressions that fill in the gaps (F). This was found while analysing the formula. No part of Kouwen's work was used to steer the GP search, it was independently discovered by GP. The equation was created on data generated by a dynamical model. After selection and analysis, the GP-induced equation and the dynamical model were tested on laboratory experiments gathered from 17 independent studies. In the comparison, the GP-expression was not significantly worse than the more complex dynamical model (E). It is important to note here that while the dynamical model needs extensive hardware to run, the GP-expression is simple enough to be used by an engineer in the field only using a pocket calculator. Currently a publication is in review for the Journal of Hydraulic Research in order to publish the formula (D). (7) citations Keijzer, M., Baptist, M., Babovic, V., Uthuruburu, J., Determining Equations for Vegetation Induced Bonabeau, E.W.; Cantu-Paz, E.; Dasgupta, D.; Deb, K.; Foster, J.A.; de Jong, E.D.; Lipson, H.; Llora, X.; Mancoridis, S.; Pelikan, M.; Raidl, G.R.; Soule, T.; Tyrrell, A.; Watson, J.-P.; Zitzler, E. (editors). Proceedings of the Genetic and Evolutionary Computation Conference GECCO-2005. New York, NY: ACM Press. Baptist, M. Modelling Floodplain Biogeomorphology DUP Science, Delft, 2005. avalaible through: http://www.library.tudelft.nl/dissertations/2940/f_203505_true_EN.html Resistance using Genetic Programming. In Beyer, H.-G.; O