title: ÐÐ¾Ð»ÑÑÐ¸Ðµ Ð´Ð°Ð½Ð½ÑÐµ Ð² Ð¿ÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ð¸ ÑÐ¿ÑÐ¾ÑÐ° Ð² ÐÐµÐ¶Ð´ÑÐ½Ð°ÑÐ¾Ð´Ð½Ð¾Ð¼ Ð°ÑÑÐ¾Ð¿Ð¾ÑÑÑ Ð¨ÐµÑÐµÐ¼ÐµÑÑÐµÐ²Ð¾
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: Big data in forecasting demand at Sheremetyevo International Airport
Creators: name: Ð¨Ð°Ð¹ÑÐ»ÐµÐµÐ²Ð°, ÐÐ°Ð·Ð¸ÑÐ°
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°Ð½Ð°Ð»Ð¸Ð· Ð´Ð°Ð½Ð½ÑÑ
Ð±Ð¾Ð»ÑÑÐ¸Ðµ Ð´Ð°Ð½Ð½ÑÐµ
Ð¿ÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ ÑÐ¿ÑÐ¾ÑÐ°
Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
catboost
data analysis
big data
demand forecasting
machine learning

description: Ð¦ÐµÐ»ÑÑ Ð´Ð°Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÑ ÑÐ²Ð»ÑÐµÑÑÑ Ð¿Ð¾Ð¸ÑÐº Ð¸ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ðµ Ð¼Ð¾Ð´ÐµÐ»Ð¸, Ð¿ÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÑÑÑÐµÐ¹ Ð¿Ð¾ÑÑÐµÐ±Ð¸ÑÐµÐ»ÑÑÐºÑÑ Ð°ÐºÑÐ¸Ð²Ð½Ð¾ÑÑÑ Ð² Ð°ÑÑÐ¾Ð¿Ð¾ÑÑÑ Ð² Ð·Ð°Ð²Ð¸ÑÐ¸Ð¼Ð¾ÑÑÐ¸ Ð¾Ñ ÑÐ°Ð·Ð»Ð¸ÑÐ½ÑÑ ÑÐ°ÐºÑÐ¾ÑÐ¾Ð². ÐÑÐ»Ð¸ ÑÐµÑÐµÐ½Ñ ÑÐ»ÐµÐ´ÑÑÑÐ¸Ðµ Ð·Ð°Ð´Ð°ÑÐ¸: â Ð¡Ð¾Ð±ÑÐ°Ð½Ñ Ð¸ Ð¿ÑÐ¾Ð°Ð½Ð°Ð»Ð¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ñ ÑÑÐ°ÑÐ¸ÑÑÐ¸ÑÐµÑÐºÐ¸Ðµ Ð´Ð°Ð½Ð½ÑÐµ Ð¾ Ð¿Ð¾ÑÑÐµÐ±Ð¸ÑÐµÐ»ÑÑÐºÐ¾Ð¹ Ð°ÐºÑÐ¸Ð²Ð½Ð¾ÑÑÐ¸ Ð¿Ð°ÑÑÐ°Ð¶Ð¸ÑÐ¾Ð² Ð² Ð°ÑÑÐ¾Ð¿Ð¾ÑÑÑ. â ÐÐ·ÑÑÐµÐ½Ð¾ Ð²Ð»Ð¸ÑÐ½Ð¸Ðµ ÑÐ°Ð·Ð»Ð¸ÑÐ½ÑÑ ÑÐ°ÐºÑÐ¾ÑÐ¾Ð² Ð½Ð° Ð¿Ð¾ÑÑÐµÐ±Ð¸ÑÐµÐ»ÑÑÐºÑÑ Ð°ÐºÑÐ¸Ð²Ð½Ð¾ÑÑÑ Ð¿Ð°ÑÑÐ°Ð¶Ð¸ÑÐ¾Ð². â ÐÐ°Ð¹Ð´ÐµÐ½Ð° Ð¸ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð° Ð¼Ð¾Ð´ÐµÐ»Ñ, ÑÑÐ¸ÑÑÐ²Ð°ÑÑÐ°Ñ Ð²ÑÐµ ÑÐ°ÐºÑÐ¾ÑÑ Ð¸ ÑÐ¿Ð¾ÑÐ¾Ð±Ð½Ð°Ñ ÑÐ¿ÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÐ¾Ð²Ð°ÑÑ Ð¿Ð¾ÑÑÐµÐ±Ð¸ÑÐµÐ»ÑÑÐºÑÑ Ð°ÐºÑÐ¸Ð²Ð½Ð¾ÑÑÑ Ð² Ð°ÑÑÐ¾Ð¿Ð¾ÑÑÑ. â Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ñ ÑÐµÐºÐ¾Ð¼ÐµÐ½Ð´Ð°ÑÐ¸Ð¸ Ð¿Ð¾ Ð¾Ð¿ÑÐ¸Ð¼Ð¸Ð·Ð°ÑÐ¸Ð¸ Ð¼Ð°ÑÐºÐµÑÐ¸Ð½Ð³Ð¾Ð²ÑÑ Ð¿ÑÐµÐ´Ð»Ð¾Ð¶ÐµÐ½Ð¸Ð¹ Ð¸ Ð¿Ð»Ð°Ð½Ð¾Ð² ÑÐ°Ð·Ð²Ð¸ÑÐ¸Ñ Ð¼Ð°ÑÑÑÑÑÐ½Ð¾Ð¹ ÑÐµÑÐ¸ Ð¸ Ð¸Ð½ÑÑÐ°ÑÑÑÑÐºÑÑÑÑ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð¿Ð¾Ð»ÑÑÐµÐ½Ð½ÑÑ Ð¿ÑÐ¾Ð³Ð½Ð¾Ð·Ð¾Ð². ÐÐºÑÑÐ°Ð»ÑÐ½Ð¾ÑÑÑ ÑÐµÐ¼Ñ Ð¾Ð±ÑÑÐ»Ð¾Ð²Ð»ÐµÐ½Ð° Ð½ÐµÐ´Ð¾ÑÑÐ°ÑÐ¾ÑÐ½Ð¾Ð¹ Ð¸Ð·ÑÑÐµÐ½Ð½Ð¾ÑÑÑÑ ÑÐ°ÐºÑÐ¾ÑÐ¾Ð², Ð²Ð»Ð¸ÑÑÑÐ¸Ñ Ð½Ð° Ð¿Ð¾ÑÑÐµÐ±Ð¸ÑÐµÐ»ÑÑÐºÑÑ Ð°ÐºÑÐ¸Ð²Ð½Ð¾ÑÑÑ Ð² Ð°ÑÑÐ¾Ð¿Ð¾ÑÑÑ Ð¨ÐµÑÐµÐ¼ÐµÑÑÐµÐ²Ð¾.Â  ÐÑÑÐ¾ÑÐ½Ð¸ÐºÐ°Ð¼Ð¸ Ð¸Ð½ÑÐ¾ÑÐ¼Ð°ÑÐ¸Ð¸ Ð²ÑÑÑÑÐ¿Ð¸Ð»Ð¸ Ð´Ð°Ð½Ð½ÑÐµ Ð¾ÑÐµÑÐµÑÑÐ²ÐµÐ½Ð½Ð¾Ð¹ Ð¸ Ð·Ð°ÑÑÐ±ÐµÐ¶Ð½Ð¾Ð¹ Ð½Ð°ÑÑÐ½Ð¾-Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°ÑÐµÐ»ÑÑÐºÐ¾Ð¹ Ð»Ð¸ÑÐµÑÐ°ÑÑÑÑ, Ð¾ÑÐ¸ÑÐ¸Ð°Ð»ÑÐ½ÑÑ ÐÐ½ÑÐµÑÐ½ÐµÑ-ÑÐµÑÑÑÑÐ¾Ð² Ð¸ Ð°Ð½Ð°Ð»Ð¸ÑÐ¸ÑÐµÑÐºÐ¸Ñ Ð°Ð³ÐµÐ½ÑÑÑÐ². ÐÐ±Ð»Ð°ÑÑÑ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ñ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð² Ð´Ð°Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÑ Ð²ÐºÐ»ÑÑÐ°ÐµÑ Ð°Ð²Ð¸Ð°ÑÐ¸Ð¾Ð½Ð½ÑÑ/Ð¶ÐµÐ»ÐµÐ·Ð½Ð¾Ð´Ð¾ÑÐ¾Ð¶Ð½ÑÑ Ð¸Ð½Ð´ÑÑÑÑÐ¸Ñ, Ð° ÑÐ°ÐºÐ¶Ðµ Ð´ÑÑÐ³Ð¸Ðµ Ð¾ÑÑÐ°ÑÐ»Ð¸, Ð¸ÑÐ¿Ð¾Ð»ÑÐ·ÑÑÑÐ¸Ðµ Ð¿ÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ ÑÐ¿ÑÐ¾ÑÐ°, ÑÐ°ÐºÐ¸Ðµ ÐºÐ°Ðº ÑÑÑÐ¸Ð·Ð¼ Ð¸ Ð³Ð¾ÑÑÐµÐ¿ÑÐ¸Ð¸Ð¼ÑÑÐ²Ð¾. ÐÑÐ²Ð¾Ð´Ñ ÑÐ°Ð±Ð¾ÑÑ Ð·Ð°ÐºÐ»ÑÑÐ°ÑÑÑÑ Ð² ÑÐ¾Ð¼, ÑÑÐ¾ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸Ðµ Ð±Ð¾Ð»ÑÑÐ¸Ñ Ð´Ð°Ð½Ð½ÑÑ ÑÐ²Ð»ÑÐµÑÑÑ Ð¿ÐµÑÑÐ¿ÐµÐºÑÐ¸Ð²Ð½ÑÐ¼ Ð¿Ð¾Ð´ÑÐ¾Ð´Ð¾Ð¼ Ð² Ð¿ÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ð¸ ÑÐ¿ÑÐ¾ÑÐ° Ð² Ð°Ð²Ð¸Ð°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð¹ Ð¸Ð½Ð´ÑÑÑÑÐ¸Ð¸ Ð¸ Ð¼Ð¾Ð¶ÐµÑ ÑÐ»ÑÑÑÐ¸ÑÑ Ð±Ð¸Ð·Ð½ÐµÑ Ð°Ð²Ð¸Ð°ÐºÐ¾Ð¼Ð¿Ð°Ð½Ð¸Ð¹.
description: The purpose of this work is to find and apply a model that predicts consumer activity at the airport depending on various factors. The following tasks were solved: âÂ  Collected and analyzed statistical data on the consumer activity of passengers at the airport. âÂ  The influence of various factors on the consumer activity of passengers has been studied. âÂ  A model has been found and applied that takes into account all factors and is able to predict consumer activity at the airport. âÂ  Recommendations have been developed to optimize marketing proposals and plans for the development of the route network and infrastructure based on the forecasts received. The relevance of the topic is due to insufficient knowledge of the factors affecting consumer activity at Sheremetyevo Airport. The sources of information were data from domestic and foreign research literature, official Internet resources and analytical agencies. The scope of application of the results of this work includes the aviation/railway industry, as well as other industries using demand forecasting, such as tourism and hospitality. The conclusions of the work are that the use of big data is a promising approach in forecasting demand in the aviation industry and can improve the efficiency of airline business.