The availability of large environmental datasets and increased computational capability has motivated researchers to propose innovative techniques to mine information from data. The Evolutionary Polynomial Regression (EPR) is a hybrid data-driven technique that combines genetic algorithms and numerical regression for developing easily interpretable mathematical model expressions. EPR is a multi-objective search paradigm for producing multiple models by simultaneously optimizing accuracy and parsimony of resulting expressions. The EPR MOGA-XL is an MS-Excel add-in that allows the user to launch an EPR run as a function in MS-Excel, thereby exploiting a familiar environment to perform data-driven modeling. Inputs and outputs can be easily selected from a spreadsheet, while a separate sheet containing all EPR modeling options can be modified and retrieved for future analyses. The expression(s) of model(s) obtained, the model predictions and fitness indicators are stored in a separate Excel file, allowing subsequent multiple analyses. An application of EPR-MOGA-XL is presented and discussed.
EPR-MOGA-XL: an excel based paradigm to enhance transfer of research achievements on data-driven modeling / Laucelli, Daniele Biagio; Berardi, Luigi; Doglioni, Angelo; Giustolisi, Orazio. - (2012). (Intervento presentato al convegno 10th International Conference on Hydroinformatics HIC 2012 tenutosi a Hamburg, Germany nel 14-18 luglio 2012).
EPR-MOGA-XL: an excel based paradigm to enhance transfer of research achievements on data-driven modeling
LAUCELLI, Daniele Biagio;BERARDI, Luigi;DOGLIONI, Angelo;GIUSTOLISI, Orazio
2012
Abstract
The availability of large environmental datasets and increased computational capability has motivated researchers to propose innovative techniques to mine information from data. The Evolutionary Polynomial Regression (EPR) is a hybrid data-driven technique that combines genetic algorithms and numerical regression for developing easily interpretable mathematical model expressions. EPR is a multi-objective search paradigm for producing multiple models by simultaneously optimizing accuracy and parsimony of resulting expressions. The EPR MOGA-XL is an MS-Excel add-in that allows the user to launch an EPR run as a function in MS-Excel, thereby exploiting a familiar environment to perform data-driven modeling. Inputs and outputs can be easily selected from a spreadsheet, while a separate sheet containing all EPR modeling options can be modified and retrieved for future analyses. The expression(s) of model(s) obtained, the model predictions and fitness indicators are stored in a separate Excel file, allowing subsequent multiple analyses. An application of EPR-MOGA-XL is presented and discussed.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

