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Embedding Measurement UNcertainty in Decision making and Optimization

This project is a multi-disciplinary effort to integrate two complementary fields of Computer Science, namely fuzzy regression analysis and constraint-based reasoning, in order to develop decision support systems for optimization... ver más

31/03/2016

USMB

75K€

Presupuesto del proyecto: 75K€

Líder del proyecto

UNIVERSITE SAVOIE MONT BLANC No se ha especificado una descripción o un objeto social para esta compañía.

Fecha límite participación Sin fecha límite de participación.

Financiación concedida El organismo FP7 notifico la concesión del proyecto el día 2016-03-31 No tenemos la información de la convocatoria

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Líder del proyecto

UNIVERSITE SAVOIE MONT BLANC No se ha especificado una descripción o un objeto social para esta compañía.

Presupuesto del proyecto 75K€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto This project is a multi-disciplinary effort to integrate two complementary fields of Computer Science, namely fuzzy regression analysis and constraint-based reasoning, in order to develop decision support systems for optimization problems permeated with measurement uncertainty. Data uncertainty due to imprecise or incomplete measurements is ubiquitous in many real world applications. Recently, models derived from fuzzy regression analysis have been defined to represent incomplete and imprecise measurements. They are mostly used in complex systems analysis seeking a correlation between crisp or fuzzy measurements. The Constraint Programming (CP) paradigm has proved successful to tackle decision and optimization problems in planning and resource optimization. Interestingly, it handles some forms of uncertainty, but has not, to our knowledge, been enhanced to deal with fuzzy regression models. Our objectives are threefold: 1) to study the theoretical aspect of integrating two complementary paradigms, 2) to design and implement an interval regression constraint system, and apply it to a case study in the field of Renewable Energies (RE) techno-economics. The decision support prototype will tackle the problem of RE portfolio optimization for short and longer term, 3) to disseminate our results at the EU and International levels. The objectives will be achieved by combining the host expertise in fuzzy regression models, and the applicant’s expertise in CP languages and optimization techniques, and her more recent works in RE techno-economics problems in Egypt. A set of three activities matching the objectives will be carried out divided into survey, design and implementation work packages and clear milestones. This project is relevant to CIG Work Programme for 3 main reasons: 1) it is a multi-disciplinary project, 2) expertise will be transferred and acquired, 3) dissemination and re-integration will enhance EU research excellence already strong in these domains.

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