енергія

The use of machine learning models for electricity consumption prediction for smart grid has been investigated. It was found that data pre-processing can improve the performance of the energy consumption prediction model, while machine learning algorithms can improve model prediction accuracy through the integration of multiple algorithms and hyperparameter optimization. It was found that the ensemble learning method can provide better prediction accuracy than each individual method by combining the strong features of different methods that have different structural characteristics.

We consider the process of forming, which is carried out by means of providing differences, through structure, color, texture and texture. Form is conceived of as a structure of elements and relationships hierarchically divided to establish a cumulative unity. Its three objective categories are mass, texture and color. It will have a fuller and more correct meaning if we understand it as a kind of “active energy”.

Predicting a building’s energy consumption plays an important role as it can help assess its energy efficiency, identify and diagnose energy system faults, and reduce costs and improve climate impact. An analysis of current research in the field of ensuring the energy efficiency of buildings, in particular, their energy assessment, considering the types of models under consideration, was carried out.

Problem setting. One of the most pressing issues of the development of the fuel and energy complex of Ukraine, the discussion about which has been going on for many years, is the question of the size, forms and directions of state intervention in the activities of individual industries and sub-sectors of the complex, as well as the assessment of the consequences of this intervention for the economy and society as a whole.

For the municipal solid waste (MSW) to be used in a proper way, it is necessary to implement clean technologies capable of thermal treatment of MSW and RDF in order to produce heat and electricity while meeting current ecological requirements. Nowadays, a number of technologies for MSW/RDF thermal treating are being used worldwide. Among them, the most proven technologies, applicable for industrial introduction, have been considered while analyzing their advantages/ disadvantages accounting for local conditions of Ukraine.

In the article describes methods of collecting, analyzing and processing of information in the case of energy supply. The systems analysis of the subject area and the conceptual model of the database and structure information support.

In this work is presented a potential of triaxial ellipsoid this help of converging rows. The koeficients which are determined integral descriptions of distributing function density of planet. This approach gives a possibility in a complex to study distributing of the masses of planet, its figure and its external gravity field.