title: ÐÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸Ðµ ÑÑÐ±Ð´ postgres Ð´Ð»Ñ ÑÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ð¸ Ð·Ð°Ð´Ð°Ñ Ð¸ÑÐºÑÑÑÑÐ²ÐµÐ½Ð½Ð¾Ð¹ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð±Ð°ÐºÐ°Ð»Ð°Ð²ÑÐ°
titleType: Subtitle
title: Using DBMS postgres to implement artificial neural network tasks
Creators: name: ÐÑÑÐ¸Ð½, Ð¤ÐµÐ´Ð¾Ñ
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: 2023
Subjects: Ð¸ÑÐºÑÑÑÑÐ²ÐµÐ½Ð½ÑÐµ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
Ð±Ð°Ð·Ñ Ð´Ð°Ð½Ð½ÑÑ
ÑÐµÐºÑÑÑÑÐ½ÑÐµ Ð¿Ð°ÑÐ°Ð¼ÐµÑÑÑ Ð¥Ð°ÑÐ°Ð»Ð¸ÐºÐ°
ÑÐ¸ÑÑÐ¾Ð²ÑÐµ Ð¾Ð±ÑÐ°Ð·Ñ
Ð¾Ð±ÐµÑÐ¿ÐµÑÐµÐ½Ð¸Ðµ Ð²Ð·Ð°Ð¸Ð¼Ð¾Ð´ÐµÐ¹ÑÑÐ²Ð¸Ñ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹ Ð¸ Ð±Ð°Ð· Ð´Ð°Ð½Ð½ÑÑ
Postgres
Python
Tensorflow
Keras
artificial neural networks
databases
Haralick texture features
digital images
providing interaction between neural networks and databases

description: ÐÐ°Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¿Ð¾ÑÐ²ÑÑÐµÐ½Ð° ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐµ Ð½Ð°Ð±Ð¾ÑÐ° ÑÑÐ½ÐºÑÐ¸Ð¹ Ð¸ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð´Ð»Ñ Ð¾Ð±ÐµÑÐ¿ÐµÑÐµÐ½Ð¸Ñ Ð²Ð·Ð°Ð¸Ð¼Ð¾Ð´ÐµÐ¹ÑÑÐ²Ð¸Ñ Ð¸ÑÐºÑÑÑÑÐ²ÐµÐ½Ð½ÑÑ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹ Ð¸ Ð±Ð°Ð· Ð´Ð°Ð½Ð½ÑÑ, Ð° ÑÐ°ÐºÐ¶Ðµ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¸Ñ ÑÐ¾Ð·Ð´Ð°Ð½Ð¸Ñ, Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð¸ ÑÐ¾ÑÑÐ°Ð½ÐµÐ½Ð¸Ñ Ñ ÑÐµÐ»ÑÑ Ð¿Ð¾Ð²ÑÑÐµÐ½Ð¸Ñ ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾ÑÑÐ¸ ÑÐ°Ð±Ð¾ÑÑ Ð¸ ÑÐ¼ÐµÐ½ÑÑÐµÐ½Ð¸Ñ Ð²ÑÐµÐ¼ÐµÐ½Ð¸, Ð·Ð°ÑÑÐ°ÑÐ¸Ð²Ð°ÐµÐ¼Ð¾Ð³Ð¾ Ð½Ð° Ð²ÑÐ¿Ð¾Ð»Ð½ÐµÐ½Ð¸Ðµ Ð±Ð¾Ð»ÑÑÐ¸Ð½ÑÑÐ²Ð° Ð·Ð°Ð´Ð°Ñ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ. Ð ÑÐ°Ð¼ÐºÐ°Ñ ÑÐ°Ð±Ð¾ÑÑ Ñ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸ÐµÐ¼ ÑÐ°ÑÑÐ¸ÑÐµÐ½Ð¸Ñ PL/Python Ð¸ ÑÑÐµÐ¹Ð¼Ð²Ð¾ÑÐºÐ° Tensorflow Ð±ÑÐ» ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½ ÑÑÐ½ÐºÑÐ¸Ð¾Ð½Ð°Ð» Ð² ÑÐ¸ÑÑÐµÐ¼Ðµ ÑÐ¿ÑÐ°Ð²Ð»ÐµÐ½Ð¸Ñ Ð±Ð°Ð·Ð°Ð¼Ð¸ Ð´Ð°Ð½Ð½ÑÑ (Ð¡Ð£ÐÐ) Postgres, Ð¿Ð¾Ð·Ð²Ð¾Ð»ÑÑÑÐ¸Ð¹ ÑÐ¾Ð·Ð´Ð°Ð²Ð°ÑÑ, Ð¾Ð±ÑÑÐ°ÑÑ, ÑÐ¾ÑÑÐ°Ð½ÑÑÑ, Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°ÑÑ Ð¸ ÑÐµÑÑÐ¸ÑÐ¾Ð²Ð°ÑÑ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸, Ð½Ð°ÑÑÑÐ°Ð¸Ð²Ð°Ñ Ð½ÐµÐ¾Ð±ÑÐ¾Ð´Ð¸Ð¼ÑÐµ Ð¿Ð°ÑÐ°Ð¼ÐµÑÑÑ Ð½Ð° ÐºÐ°Ð¶Ð´Ð¾Ð¼ ÑÑÐ°Ð¿Ðµ. Ð¢Ð°ÐºÐ¾Ð¹ Ð½Ð°Ð±Ð¾Ñ ÑÑÐ½ÐºÑÐ¸Ð¹ Ð¸ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¼Ð¾Ð¶ÐµÑ Ð±ÑÑÑ Ð¸Ð½ÑÐµÐ³ÑÐ¸ÑÐ¾Ð²Ð°Ð½ Ð² ÐºÐ»Ð¸ÐµÐ½Ñ-ÑÐµÑÐ²ÐµÑÐ½ÑÑ ÑÐ¸ÑÑÐµÐ¼Ñ Ð¸ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°ÑÑÑÑ Ð² Ð¿ÑÐ¾Ð¼ÑÑÐ»ÐµÐ½Ð½Ð¾Ð¼ Ð¼Ð°ÑÑÑÐ°Ð±Ðµ Ð´Ð»Ñ Ð°Ð²ÑÐ¾Ð¼Ð°ÑÐ¸Ð·Ð°ÑÐ¸Ð¸ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹. ÐÐ»Ñ Ð´ÐµÐ¼Ð¾Ð½ÑÑÑÐ°ÑÐ¸Ð¸ ÑÐ°Ð±Ð¾ÑÑ ÑÐµÐ°Ð»Ð¸Ð·Ð¾Ð²Ð°Ð½Ð½ÑÐ¹ ÑÑÐ½ÐºÑÐ¸Ð¾Ð½Ð°Ð» Ð¸ÑÐ¿Ð¾Ð»ÑÐ·ÑÐµÑÑÑ Ð¿ÑÐ¸ ÑÐ¾Ð·Ð´Ð°Ð½Ð¸Ð¸ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸ Ð¿ÑÑÐ¼Ð¾Ð³Ð¾ ÑÐ°ÑÐ¿ÑÐ¾ÑÑÑÐ°Ð½ÐµÐ½Ð¸Ñ Ð´Ð»Ñ Ð²ÑÑÐ²Ð»ÐµÐ½Ð¸Ñ Ð±Ð¾Ð»ÐµÐ·Ð½ÐµÐ¹ Ð¿ÑÐµÐ½Ð¸ÑÑ, Ñ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸ÐµÐ¼ ÑÐµÑÐ½Ð¾Ð»Ð¾Ð³Ð¸Ð¸ ÑÐ¾Ð·Ð´Ð°Ð½Ð¸Ñ ÑÐ¸ÑÑÐ¾Ð²ÑÑ Ð¾Ð±ÑÐ°Ð·Ð¾Ð² Ð¿Ð¾ Ð¸Ð¼ÐµÑÑÐ¸Ð¼ÑÑ Ð½Ð°Ð±Ð¾ÑÐ°Ð¼ Ð´Ð°Ð½Ð½ÑÑ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ ÑÐµÐºÑÑÑÑÐ½ÑÑ Ð¿Ð°ÑÐ°Ð¼ÐµÑÑÐ¾Ð² Ð¥Ð°ÑÐ°Ð»Ð¸ÐºÐ°. Ð ÑÐ¾Ð´Ðµ ÑÐ°Ð±Ð¾ÑÑ Ð¿ÑÐ¾Ð¸Ð·Ð²Ð¾Ð´Ð¸ÑÑÑ ÑÑÐ°Ð²Ð½ÐµÐ½Ð¸Ðµ ÑÐºÐ¾ÑÐ¾ÑÑÐ¸ Ð²ÑÐ¿Ð¾Ð»Ð½ÐµÐ½Ð¸Ñ Ð²ÑÐµÑ ÑÑÐ°Ð¿Ð¾Ð² Ð¼ÐµÐ¶Ð´Ñ ÑÑÐ½ÐºÑÐ¸Ð¾Ð½Ð°Ð»Ð¾Ð¼ Ð¸ ÑÑÐ°Ð½Ð´Ð°ÑÑÐ½ÑÐ¼Ð¸ Ð¼ÐµÑÐ¾Ð´Ð°Ð¼Ð¸ Ð½Ð° ÑÐ·ÑÐºÐµ Python.
description: This work is devoted to developing a set of functions and methods to provide the interaction of artificial neural networks and databases, as well as research methods of its creation, training and saving to improve performance and reduce the time required to perform most of the machine-learning tasks. In this work, using the PL/Python extension and the Tensorflow framework, a functionality was developed in the Postgres database management system (DBMS) to create, train, save, use, and test neural networks by configuring the necessary parameters at each step. This set of functions and methods can be integrated into a client-server system and used on an industrial scale to automate the training of neural networks. To demonstrate the work, the implemented functionality is used to create a forward propagation neural network for the detection of wheat diseases, using the technology of digital image creation from the available datasets based on the textural Haralick parameters. In the process of work the speed of execution of all steps between the implemented functional and standard methods in the Python language is compared.