Development of an innovative single system for the registration and archiving of data intended for use in energy networks by carrying out research and development work on innovative algorithms for predictive interference based on neural network theory, enabling the analysis of the data collected in the development of the system to be developed in order to improve the reliability of the system en (Q122718): Difference between revisions
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(Removed claim: summary (P836): The aim of the project is to develop an innovative system for the recording and archiving of the data of the HDC (Historical Data Concentrator) for the use in energy networks of R & D by developing and conducting research into innovative prediction algorithms based on neural network theory, to analyse the data collected in the design of the registration system that is being developed, in order to improve the reliability of the energy system an...) |
(Created claim: summary (P836): The aim of the project is to develop an innovative system for recording and archiving HDC data (Historical Data concentrator) intended for use in energy networks to carry out R & D work by developing and conducting research into innovative algorithms for predicting interference based on neural network theory, enabling the analysis of collected data in the developed registration system to improve the reliability of the energy system and reduce lo...) |
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The aim of the project is to develop an innovative system for recording and archiving HDC data (Historical Data concentrator) intended for use in energy networks to carry out R & D work by developing and conducting research into innovative algorithms for predicting interference based on neural network theory, enabling the analysis of collected data in the developed registration system to improve the reliability of the energy system and reduce losses by reducing the time of shutdowns. The key component of the project will be algorithms based on the theory of neural networks, which will allow the analysis of archived data under the prediction of behaviour of the energy system. The neural network can be taught in such a way that it will become a model of the energy system under consideration, so that it will be possible to predict the preservation of the energy grid. This can be used to supervise the operation of the energy system as well as for system failure. (English) | |||||||||||||||
| Property / summary: The aim of the project is to develop an innovative system for recording and archiving HDC data (Historical Data concentrator) intended for use in energy networks to carry out R & D work by developing and conducting research into innovative algorithms for predicting interference based on neural network theory, enabling the analysis of collected data in the developed registration system to improve the reliability of the energy system and reduce losses by reducing the time of shutdowns. The key component of the project will be algorithms based on the theory of neural networks, which will allow the analysis of archived data under the prediction of behaviour of the energy system. The neural network can be taught in such a way that it will become a model of the energy system under consideration, so that it will be possible to predict the preservation of the energy grid. This can be used to supervise the operation of the energy system as well as for system failure. (English) / rank | |||||||||||||||
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| Property / summary: The aim of the project is to develop an innovative system for recording and archiving HDC data (Historical Data concentrator) intended for use in energy networks to carry out R & D work by developing and conducting research into innovative algorithms for predicting interference based on neural network theory, enabling the analysis of collected data in the developed registration system to improve the reliability of the energy system and reduce losses by reducing the time of shutdowns. The key component of the project will be algorithms based on the theory of neural networks, which will allow the analysis of archived data under the prediction of behaviour of the energy system. The neural network can be taught in such a way that it will become a model of the energy system under consideration, so that it will be possible to predict the preservation of the energy grid. This can be used to supervise the operation of the energy system as well as for system failure. (English) / qualifier | |||||||||||||||
point in time: 21 October 2020
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Revision as of 10:09, 21 October 2020
Project in Poland financed by DG Regio
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Development of an innovative single system for the registration and archiving of data intended for use in energy networks by carrying out research and development work on innovative algorithms for predictive interference based on neural network theory, enabling the analysis of the data collected in the development of the system to be developed in order to improve the reliability of the system en |
Project in Poland financed by DG Regio |
Statements
765,578.03 zloty
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1,570,255.44 zloty
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48.75 percent
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1 May 2018
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31 July 2020
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VOLEN SPÓŁKA AKCYJNA
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Celem projektu jest opracowanie innowacyjnego systemu rejestracji i archiwizacji danych HDC (Historical Data Concentrator) przeznaczonego do stosowania w sieciach energetycznych przeprowadzenie prac B+R poprzez opracowanie i przeprowadzenie badań nad innowacyjnymi algorytmami predykcji zakłóceń opartych na teorii sieci neuronowych, umożliwiających analizę zebranych danych w opracowywanym systemie rejestracji w celu poprawienia niezawodności systemu energetycznego i zmniejszeniu strat przez redukcję czasu wyłączeń. Kluczowym elementem składowym projektu będą algorytmy oparte na teorii sieci neuronowych, które umożliwią analizę archiwizowanych danych pod kontem predykcji zachowania się systemu energetycznego. Sieć neuronowa może zostać w taki sposób nauczona, że stanie się modelem rozpatrywanego systemu energetycznego, dzięki czemu będzie możliwe przewidzenie zachowania sieci energetycznej. Można to wykorzystać do nadzoru nad pracą systemu energetycznego, jak również do awarii systemu. (Polish)
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The aim of the project is to develop an innovative system for recording and archiving HDC data (Historical Data concentrator) intended for use in energy networks to carry out R & D work by developing and conducting research into innovative algorithms for predicting interference based on neural network theory, enabling the analysis of collected data in the developed registration system to improve the reliability of the energy system and reduce losses by reducing the time of shutdowns. The key component of the project will be algorithms based on the theory of neural networks, which will allow the analysis of archived data under the prediction of behaviour of the energy system. The neural network can be taught in such a way that it will become a model of the energy system under consideration, so that it will be possible to predict the preservation of the energy grid. This can be used to supervise the operation of the energy system as well as for system failure. (English)
21 October 2020
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Identifiers
RPSL.01.02.00-24-061G/17
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