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Abstract-This article is reviews some aspects of information management in health service. The concept of "quality of medical care" is considered. The features of the unified information space is represented. The conceptual scheme of management system with the use of artificial intelligence is suggested. The algorithm of neural network learning using back-propagation procedure is analyzed.Keywords-health service, quality of medical care, information technology, common information space, artificial intelligence, neural networks

The relevance of the work lies in the application of universal image processing for further verification of data. The use of pattern recognition makes it possible to quickly identify errors in the manual entry of various information. The object of the research is business processes aimed at detailed monitoring and metering of electric power of IDGC of Center and Volga Region, PJSC, Udmurtenergo branch. Subject of research - the principles of design and practical application of the intellectual system in the enterprise. The aim of the work is to increase the level of reliability of commercial accounting of electricity. Development of the Intellectual Information System for Electric Power Metering (IISEPM) by applying the data collection terminals has been proposed in order to solve the problem of mobile electricity metering. The implementation of IISEPM will reduce commercial losses and improve the observability and controllability of the power grid infrastructure. For enterprises, which activities are aimed at providing services for the electricity transmission to a large number of consumers, it is important to have an accurate idea of the number of the provided services. In the modern conditions, it is possible to automate the process of collecting information, so that in the future it will be possible to verify the received data in a single processing center. Taking readings from metering devices is a necessary monthly procedure. The traditional way is that the consumer writes down the meter readings on paper, and then also manually calculates the amount of energy spent per month. The next step for the consumer is to transfer the readings taken from the power sales company, where employees record the meter readings and then also manually calculates the amount of energy spent per month. The next step for the consumer is to transfer the readings taken from the power sales company, where employees record the meter readings in the database. The user has the right to transfer data remotely by logging into his personal account on the company’s website. The power supply company, having received the consumer’s data, calculates the cost of the electricity consumed at a certain tariff and notifies the consumer about it, sending him a receipt of payment. Automation will reduce the amount of paper media. The human factor will also be excluded, which will increase the accuracy of the calculated energy consumption and, therefore, the inadmissibility of emergency situations will be achieved. Index Terms—convolutional neural network, data collection terminal, information-analytical complex, intelligent information mobile system, mobile energy accounting, pattern recognition, service-oriented architecture, Viola-Jones method.

The article substantiates the relevance of optimization algorithms research for solving various applied problems and for the science of artificial intelligence. The need to solve problems of optimizing the thermal-hydraulic modes of buildings (as part of the project "Smart City") is explained. The paper presents a mathematical formulation of the problem of optimizing the temperature mode of rooms using adjustable devices. Existing work provides two methods for solving the posed problem. They are the coordinates search method and the genetic algorithm. The article contains the description of the above mentioned algorithms (including the mathematical apparatus used). The results of the computational experiment (for the considered optimization methods) are presented. These experimental results show that the genetic algorithm provides better optimization results than the coordinates search method, but it has a large computational cost. The hypothesis was confirmed that in order to increase the efficiency of solving the considered class of problems it is necessary to combine the genetic algorithm and the coordinates search method.

The article discusses the use of mathematical modeling and system analysis methods to solve problems of water preparation. Models for predicting indicators of drinking water based on the quality of the source water are proposed. The technological process of deodorization of drinking water is considered. The following system analysis methods were used in the models development: correlation analysis of data, the principal component method, regression modeling, and the least squares method. Hidden relationships between indicators of drinking and source water were identified. The adequacy of the obtained results was proved by comparing them with the actual values. The obtained results approximate well the actual values. The results can be used in water supply systems to improve the quality of drinking water.