1,721,001 research outputs found
Decision Support for Water Distribution System Rehabilitation Using Evolutionary Computing
No full textAdvances in Data-Driven Analyses and Modelling Using EPR-MOGA
No full textEvolutionary Polynomial Regression (EPR) is a recently developed hybrid regression method that combines the best features of conventional numerical regression techniques with the genetic programming/symbolic regression technique. The original version of EPR works with formulae based on true or pseudo-polynomial expressions using a single-objective genetic algorithm. Therefore, to obtain a set of formulae with a variable number of pseudo-polynomial coefficients, the sequential search is performed in the formulae space. This article presents an improved EPR strategy that uses a multi-objective genetic algorithm instead. We demonstrate that multi-objective approach is a more feasible instrument for data analysis and model selection. Moreover, we show that EPR can also allow for simple uncertainty analysis (since it returns polynomial structures that are linear with respect to the estimated coefficients). The methodology is tested and the results are reported in a case study relating groundwater level predictions to total month-ly rainfall
A multi-model approach to analysis of environmental phenomena
No full textA 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. Multipurpose 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
Asset performance analysis using multi-utility data and multi-objective data mining techniques
No full textData Mining for Management and Rehabilitation of Water Systems: The Evolutionary Polynomial Regression Approach
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