Training and modernisation of public administrations and services – SATDAP – Training of Public Administration (Q2913556): Difference between revisions
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(Changed label, description and/or aliases in en: translated_label) |
(Removed claim: summary (P836): The IA-SI project aims to improve risk management in the analysis phase of payment requests from beneficiaries of Portugal 2020 incentive systems, using machine learning techniques. The aim is to develop solutions based on forecasting models on the reliability of eligibility of expenditure and on anticipating risks of meeting targets, to be used in the management of incentives., remove_old_english_translation) |
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| Property / summary: The IA-SI project aims to improve risk management in the analysis phase of payment requests from beneficiaries of Portugal 2020 incentive systems, using machine learning techniques. The aim is to develop solutions based on forecasting models on the reliability of eligibility of expenditure and on anticipating risks of meeting targets, to be used in the management of incentives. (English) / rank | |||||||||||||||
| Property / summary: The IA-SI project aims to improve risk management in the analysis phase of payment requests from beneficiaries of Portugal 2020 incentive systems, using machine learning techniques. The aim is to develop solutions based on forecasting models on the reliability of eligibility of expenditure and on anticipating risks of meeting targets, to be used in the management of incentives. (English) / qualifier | |||||||||||||||
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Revision as of 13:36, 8 July 2021
Project Q2913556 in Portugal
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Training and modernisation of public administrations and services – SATDAP – Training of Public Administration |
Project Q2913556 in Portugal |
Statements
254,972.96 Euro
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85.0 percent
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1 January 2020
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30 September 2021
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IAPMEI - AGÊNCIA PARA A COMPETITIVIDADE E INOVAÇÃO, I.P.
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Q2986199 (Deleted Item)
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41°8'58.02"N, 8°36'38.84"W
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O projeto IA-SI tem por objetivo melhorar a gestão dos riscos na fase de análise de pedidos de pagamento dos beneficiários dos sistemas de incentivos do Portugal 2020, com recurso a técnicas de aprendizagem automática. Pretende-se desenvolver soluções baseadas em modelos de previsão sobre fiabilidade de elegibilidade de despesas e sobre antecipação de riscos de cumprimento de objetivos, a utilizar na gestão de incentivos. (Portuguese)
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Porto
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Identifiers
POCI-05-5762-FSE-000231
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