title: Ð Ð°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ðµ Ð²Ð¾Ð·Ð´ÑÑÐ½ÑÑ Ð¾Ð±ÑÐµÐºÑÐ¾Ð² Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ Ð¸ÑÐºÑÑÑÑÐ²ÐµÐ½Ð½Ð¾Ð¹ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸ Ð´Ð»Ñ ÑÐ¿ÑÐ°Ð²Ð»ÐµÐ½Ð¸Ñ Ð²Ð¾Ð·Ð´ÑÑÐ½ÑÐ¼ Ð´Ð²Ð¸Ð¶ÐµÐ½Ð¸ÐµÐ¼
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: Airborne object recognition with artificial neural network for air traffic control
Creators: name: Ð¤ÑÑÐ»ÑÐ³Ð¸Ð½, ÐÐ½ÑÐ¾Ð½
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: 2021
Subjects: Ð¸ÑÐºÑÑÑÑÐ²ÐµÐ½Ð½ÑÐ¹ Ð¸Ð½ÑÐµÐ»Ð»ÐµÐºÑ
Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
Ð¸ÑÐºÑÑÑÑÐ²ÐµÐ½Ð½ÑÐµ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
tensorflow
python 3
artificial intelligence
machine learning
artificial neural networks

description: ÐÐ¾ÑÑÐ°Ð²Ð»ÐµÐ½Ð½Ð°Ñ Ð² Ð±Ð°ÐºÐ°Ð»Ð°Ð²ÑÑÐºÐ¾Ð¹ ÑÐ°Ð±Ð¾ÑÐµ Ð·Ð°Ð´Ð°ÑÐ° â ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð¼Ð¾Ð´ÐµÐ»Ð¸ Ð¸ÑÐºÑÑÑÑÐ²ÐµÐ½Ð½Ð¾Ð¹ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸ Ð´Ð»Ñ ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ñ Ð²Ð¾Ð·Ð´ÑÑÐ½ÑÑ Ð¾Ð±ÑÐµÐºÑÐ¾Ð². Ð Ð´Ð°Ð½-Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÐµ Ð¾ÑÑÑÐµÑÑÐ²Ð»ÑÐ»ÑÑ Ð²ÑÐ±Ð¾Ñ ÑÐ°ÑÐ°ÐºÑÐµÑÐ¸ÑÑÐ¸Ðº Ð²Ð¾Ð·Ð´ÑÑÐ½ÑÑ Ð¾Ð±ÑÐµÐºÑÐ¾Ð², Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ ÐºÐ¾ÑÐ¾ÑÑÑ ÐÐÐ¡ Ð±ÑÐ´ÐµÑ Ð¾Ð±ÑÑÐ°ÑÑÑÑ. ÐÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ñ Ð² ÐºÐ°ÑÐµÑÑÐ²Ðµ Ð²ÑÐ¾Ð´Ð½ÑÑ Ð¿ÑÐ¸Ð·Ð½Ð°ÐºÐ¾Ð² Ð³ÐµÐ¾Ð¼ÐµÑÑÐ¸ÑÐµÑÐºÐ¸Ðµ Ð¿Ð°ÑÐ°Ð¼ÐµÑÑÑ Ð²Ð¾Ð·Ð´ÑÑÐ½ÑÑ Ð¾Ð±ÑÐµÐºÑÐ¾Ð² Ð¸ Ð¸Ñ ÑÐºÐ¾ÑÐ¾ÑÑÐ½ÑÐµ ÑÐ°ÑÐ°ÐºÑÐµÑÐ¸ÑÑÐ¸ÐºÐ¸. Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ð° ÑÐ¿ÐµÑÐ¸Ð°Ð»ÑÐ½Ð°Ñ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð° ÑÐ±Ð¾ÑÐ° Ð´Ð°Ð½Ð½ÑÑ Ð¸Ð· ÑÐ»ÐµÐºÑÑÐ¾Ð½Ð½Ð¾Ð³Ð¾ ÑÐµÑÑÑÑÐ°, Ñ. Ðµ. Ð¿ÑÐ¾ÑÐµÑÑ ÑÐ¾ÑÑÐ°Ð²Ð»ÐµÐ½Ð¸Ñ Ð±Ð°Ð·Ñ Ð´Ð°Ð½Ð½ÑÑ Ð±ÑÐ» Ð°Ð²ÑÐ¾Ð¼Ð°ÑÐ¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½. ÐÐ·ÑÑÐµÐ½Ñ ÑÐµÐ¾ÑÐµÑÐ¸ÑÐµÑÐºÐ¸Ðµ Ð¼Ð°ÑÐµÑÐ¸Ð°Ð»Ñ Ð¾Ð± Ð¸ÑÐºÑÑÑÑÐ²ÐµÐ½Ð½ÑÑ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÑÑ. ÐÐ¿ÑÐµÐ´ÐµÐ»ÐµÐ½Ð° ÑÑÐ½ÐºÑÐ¸Ñ ÐºÐ°ÑÐµÐ³Ð¾ÑÐ¸Ð°Ð»ÑÐ½Ð¾Ð¹ ÐºÑÐ¾ÑÑ-ÑÐ½ÑÑÐ¾Ð¿Ð¸Ð¸, ÐºÐ°Ðº ÑÑÐ½ÐºÑÐ¸Ñ Ð¿Ð¾ÑÐµÑÑ Ð¸ Ð²ÑÐ±ÑÐ°Ð½ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼ Ð³ÑÐ°Ð´Ð¸ÐµÐ½ÑÐ½Ð¾Ð³Ð¾ ÑÐ¿ÑÑÐºÐ° Ð´Ð»Ñ Ð¾Ð¿ÑÐ¸Ð¼Ð¸Ð·Ð°ÑÐ¸Ð¸. Ð Ð°Ð·ÑÐ°Ð±Ð°ÑÑÐ²Ð°Ð»Ð°ÑÑ Ð¼Ð¾Ð´ÐµÐ»Ñ Ð¸ÑÐºÑÑÑÑÐ²ÐµÐ½Ð½Ð¾Ð¹ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸ Ð´Ð»Ñ ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ñ Ð²Ð¾Ð·Ð´ÑÑÐ½ÑÑ Ð¾Ð±ÑÐµÐºÑÐ¾Ð². ÐÐ¾Ð´ÐµÐ»Ñ Ð±ÑÐ»Ð° Ð¾Ð±ÑÑÐµÐ½Ð° Ð¸ Ð¿ÑÐ¾ÑÐµÑÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð°. ÐÑÑÑÐµÑÑÐ²Ð»ÐµÐ½Ñ Ð°Ð½Ð°Ð»Ð¸Ð· Ð¾ÑÐ¸Ð±Ð¾Ðº Ð¸ Ð¾ÑÐµÐ½ÐºÐ° ÐºÐ°ÑÐµÑÑÐ²Ð° Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ Ð¼Ð°ÑÑÐ¸ÑÑ Ð¾ÑÐ¸Ð±Ð¾Ðº Ð¸ ROC-ÐºÑÐ¸Ð²ÑÑ.
description: The task set in the bachelor's work is the development of a model of an artificial neural network for recognizing air objects. In this work, the choice of characteristics of air objects was carried out, on the basis of which the ANN will be trained. Geometric parameters of air objects and their speed characteristics were used as input features. A special program for collecting data from an electronic resource has been developed, that is, the process of compiling a database has been automated. Studied theoretical materials about artificial neural networks. The categorical cross-entropy function is defined as a loss function and a gradient descent algorithm is selected for optimization. A model of an artificial neural network for recognizing airborne objects was developed. The model has been trained and tested. Error analysis and quality assessment were carried out using the error matrix and ROC curves.