Abstract
The paper proposes an alternative approach to the problem of district heating monitoring parameters selection, based on conditions, taken, for instance, from a specific real district heating network supplemented with tests data and expert knowledge.
Highlights
According to the provisions of Kyoto Protocol, it is necessary to take actions against climate change and international cooperation for sustainable development on a global level
In the partial neural model built on the basis of the data obtained from computer simulation of the heating system, Variant IV is acceptable, in which the parameters measured in telemetry chambers Nos 13, 07, 08 and 12 were removed
In the partial neural model built on the basis of the data obtained from tested heating system, Variant III is acceptable, in which the parameters measured in telemetry chambers Nos 13, 07 and 08 were removed
Summary
According to the provisions of Kyoto Protocol, it is necessary to take actions against climate change and international cooperation for sustainable development on a global level. The artificial neural networks are perfectly suited for this purpose They have many features distinguishing them from other data processing systems. The most important of these features are: ability to work effectively even when they are partly damaged, ability to make generalization, interpolation and prediction, as well as little susceptibility to errors in data sets Due to their features, the artificial neural networks make it possible to create mathematical models of systems with complicated structure, which operate in a manner that cannot be fully anticipated. The artificial neural networks make it possible to create mathematical models of systems with complicated structure, which operate in a manner that cannot be fully anticipated As a result, this tool is extensively used to conduct research in many fields of science.
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