title: ÐÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ðµ Ð²Ð¾Ð·Ð¼Ð¾Ð¶Ð½Ð¾ÑÑÐµÐ¹ Ð¿Ð¾ Ð²Ð·Ð°Ð¸Ð¼Ð¾Ð´ÐµÐ¹ÑÑÐ²Ð¸Ñ Ñ Ð¼Ð¾Ð´ÐµÐ»ÑÑ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸, ÑÐ°Ð·Ð¼ÐµÑÐµÐ½Ð½Ð¾Ð¹ Ð² Ð±Ð°Ð·Ðµ Ð´Ð°Ð½Ð½ÑÑ
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Research of the opportunities for interaction with the model of the neural network placed in database
Creators: name: ÐÑÐ¾ÑÐ¾ÑÐ¾Ð², ÐÐ°ÐºÑÐ¸Ð¼
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2022
Subjects: ÐÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
ÐÐ°Ð·Ñ Ð´Ð°Ð½Ð½ÑÑ
Ñ ÑÐ°Ð½Ð¸Ð¼Ð°Ñ Ð¿ÑÐ¾ÑÐµÐ´ÑÑÐ°
stored procedure

description: Ð¢ÐµÐ¼Ð° Ð²ÑÐ¿ÑÑÐºÐ½Ð¾Ð¹ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÑ: Â«ÐÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ðµ Ð²Ð¾Ð·Ð¼Ð¾Ð¶Ð½Ð¾ÑÑÐµÐ¹ Ð¿Ð¾ Ð²Ð·Ð°Ð¸Ð¼Ð¾Ð´ÐµÐ¹ÑÑÐ²Ð¸Ñ Ñ Ð¼Ð¾Ð´ÐµÐ»ÑÑ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸, ÑÐ°Ð·Ð¼ÐµÑÐµÐ½Ð½Ð¾Ð¹ Ð² Ð±Ð°Ð·Ðµ Ð´Ð°Ð½Ð½ÑÑÂ». ÐÐ°Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¿Ð¾ÑÐ²ÑÑÐµÐ½Ð° ÑÐ¿Ð¾ÑÐ¾Ð±Ð°Ð¼ ÑÐ¾Ð²Ð¼ÐµÑÑÐ½Ð¾Ð³Ð¾ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸Ñ Ð¸ÑÐºÑÑÑÑÐ²ÐµÐ½Ð½ÑÑ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹ Ð¸ Ð±Ð°Ð· Ð´Ð°Ð½Ð½ÑÑ. ÐÐ²ÑÐ¾ÑÐ¾Ð¼ Ð±ÑÐ» Ð¿ÑÐ¾Ð¸Ð·Ð²ÐµÐ´ÐµÐ½ Ð¾Ð±Ð·Ð¾Ñ ÑÑÑÐµÑÑÐ²ÑÑÑÐ¸Ñ ÑÐµÑÐµÐ½Ð¸Ð¹ Ð¸ Ð¿Ð¾Ð´ÑÐ¾Ð´Ð¾Ð² Ð² ÑÑÐµÑÐµ Ð²Ð·Ð°Ð¸Ð¼Ð¾Ð´ÐµÐ¹ÑÑÐ²Ð¸Ñ Ñ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐ¼Ð¸ ÑÐµÑÑÐ¼Ð¸, Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ ÐºÐ¾ÑÐ¾ÑÐ¾Ð³Ð¾ Ð¿ÑÐµÐ´ÑÑÐ°Ð²Ð»ÐµÐ½Ð° ÑÐ°ÑÐ°ÐºÑÐµÑÐ¸ÑÑÐ¸ÐºÐ° ÑÐ°ÑÑÐ¼Ð¾ÑÑÐµÐ½Ð½ÑÑ ÑÑÐµÐ´ÑÑÐ². Ð¦ÐµÐ»ÑÑ ÑÐ°Ð±Ð¾ÑÑ ÑÐ²Ð»ÑÐµÑÑÑ Ð¿Ð¾Ð»ÑÑÐµÐ½Ð¸Ðµ ÑÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ð¸ ÑÐ¸ÑÑÐµÐ¼Ñ ÑÑÐ°Ð½ÐµÐ½Ð¸Ñ Ð¸ÑÐºÑÑÑÑÐ²ÐµÐ½Ð½Ð¾Ð¹ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸ Ð² Ð±Ð°Ð·Ðµ Ð´Ð°Ð½Ð½ÑÑ Ð½Ð° ÑÐµÑÐ²ÐµÑÐµ. Ð Ð¿ÑÐµÐ´Ð»Ð¾Ð¶ÐµÐ½Ð½Ð¾Ð¹ Ð°Ð²ÑÐ¾ÑÐ¾Ð¼ ÑÐ¸ÑÑÐµÐ¼Ðµ Ð¼Ð¾Ð´ÐµÐ»Ñ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸ Ð¸ Ð´Ð°Ð½Ð½ÑÐµ Ð´Ð»Ñ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð¿Ð¾Ð»Ð½Ð¾ÑÑÑÑ ÑÑÐ°Ð½ÑÑÑÑ Ð² Ð±Ð°Ð·Ðµ Ð´Ð°Ð½Ð½ÑÑ PostgreSQL. ÐÐ° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð²Ð¾Ð·Ð¼Ð¾Ð¶Ð½Ð¾ÑÑÐµÐ¹ Ð¡Ð£ÐÐ Ð±ÑÐ» ÑÐµÐ°Ð»Ð¸Ð·Ð¾Ð²Ð°Ð½ ÑÐ¿Ð¾ÑÐ¾Ð± Ð²Ð·Ð°Ð¸Ð¼Ð¾Ð´ÐµÐ¹ÑÑÐ²Ð¸Ñ Ð¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°ÑÐµÐ»Ñ Ñ Ð¼Ð¾Ð´ÐµÐ»ÑÑ Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ ÑÑÐ°Ð½Ð¸Ð¼ÑÑ Ð¿ÑÐ¾ÑÐµÐ´ÑÑ Ð½Ð° ÑÐ·ÑÐºÐµ pl/python. ÐÐ°Ð½Ð½Ð°Ñ Ð¼ÐµÑÐ¾Ð´Ð¸ÐºÐ° Ð¿Ð¾Ð·Ð²Ð¾Ð»ÑÐµÑ ÐºÐ»Ð¸ÐµÐ½ÑÑ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°ÑÑ ÑÐ¾Ð»ÑÐºÐ¾ Ð¾Ð±Ð¾Ð»Ð¾ÑÐºÑ Ð¸Ð»Ð¸ API Ð´Ð»Ñ Ð²Ð·Ð°Ð¸Ð¼Ð¾Ð´ÐµÐ¹ÑÑÐ²Ð¸Ñ Ñ Ð±Ð°Ð·Ð¾Ð¹ Ð´Ð°Ð½Ð½ÑÑ Ð¸ Ð½Ðµ ÑÐ°Ð·Ð¼ÐµÑÐ°ÑÑ Ð½Ð° Ð»Ð¾ÐºÐ°Ð»ÑÐ½Ð¾Ð¼ ÑÑÑÑÐ¾Ð¹ÑÑÐ²Ðµ ÑÑÐµÐ´ÑÑÐ²Ð° Ð´Ð»Ñ ÑÐ°Ð±Ð¾ÑÑ Ñ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐ¼Ð¸ ÑÐµÑÑÐ¼Ð¸. ÐÐ¾Ð»ÑÑÐµÐ½Ð½Ð°Ñ ÑÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ñ Ð±ÑÐ»Ð° Ð¿ÑÐ¾ÑÐµÑÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð° Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹ Ð² ÑÐ²ÐµÑÑÐ¾ÑÐ½Ð¾Ð¹ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸ Ð¸ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ ÑÐµÐºÑÑÑÑÐ½ÑÑ Ð¿ÑÐ¸Ð·Ð½Ð°ÐºÐ¾Ð² Ð¥Ð°ÑÐ°Ð»Ð¸ÐºÐ° Ð² Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸ Ð¿ÑÑÐ¼Ð¾Ð³Ð¾ ÑÐ°ÑÐ¿ÑÐ¾ÑÑÑÐ°Ð½ÐµÐ½Ð¸Ñ. Ð¢ÐµÑÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð¸ ÑÑÐ°Ð²Ð½ÐµÐ½Ð¸Ðµ Ñ Ð°Ð½Ð°Ð»Ð¾Ð³Ð¸ÑÐ½Ð¾Ð¹ ÑÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸ÐµÐ¹ Ð»Ð¾ÐºÐ°Ð»ÑÐ½Ð¾Ð³Ð¾ Ð²Ð·Ð°Ð¸Ð¼Ð¾Ð´ÐµÐ¹ÑÑÐ²Ð¸Ñ Ñ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÑÑ ÑÐ´Ð¾Ð²Ð»ÐµÑÐ²Ð¾ÑÐ¸Ð»Ð¸ ÑÑÐ¾ÑÐ¼Ð¸ÑÐ¾Ð²Ð°Ð½Ð½ÑÐ¼ ÑÑÐµÐ±Ð¾Ð²Ð°Ð½Ð¸ÑÐ¼ Ð¿Ð¾ ÑÐ°Ð·Ð¼ÐµÑÐµÐ½Ð¸Ñ Ð¸ Ð¿ÑÐ¾Ð¸Ð·Ð²Ð¾Ð´Ð¸ÑÐµÐ»ÑÐ½Ð¾ÑÑÐ¸ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸ Ð¸ Ð·Ð°Ð½Ð¸Ð¼Ð°ÐµÐ¼Ð¾Ð¹ ÐµÐ¹ Ð¿Ð°Ð¼ÑÑÑÑ.
description: The subject of the graduate qualification work is Â«Research of the opportunities for interaction with the model of the neural network placed in databaseÂ». This work is devoted to ways of sharing artificial neural networks and databases. The author made a review of existing solutions and approaches in the field of interaction with neural networks, based on which the characteristics of the considered tools are presented. The goal of the work is to obtain an implementation of an artificial neural network storage system in a database on server. In the system suggested by author, the neural network model and training data are completely stored in the PostgreSQL database. Based on capabilities of the DBMS, a way for user interaction with the model using stored procedures in pl/python language was implemented. This technique allows the client to use only an IDE or API to interact with the database and not install tools for working with neural network on the local device. The final implementation was tested based on image classification in a convolutional neural network and classification of Haralick Texture features in feed-forward neural network. Testing and comparison with a similar implementation of local interaction with a neural network satisfied the formed requirements for the placement and performance of the neural network and the memory it occupies.