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Ð”Ð°Ð½Ð½Ð°Ñ Ñ€Ð°Ð±Ð¾Ñ‚Ð° поÑвÑщена автоматизации процеÑÑа Ð¿Ð¾Ð´Ð´ÐµÑ€Ð¶Ð°Ð½Ð¸Ñ Ñ‚ÐµÐ¼Ð¿ÐµÑ€Ð°Ñ‚ÑƒÑ€Ñ‹ в транÑпортном трубопроводе на оÑнове вывода регреÑÑионной формулы Ð´Ð»Ñ Ð¿Ð¾Ð´Ð¾Ð³Ñ€ÐµÐ²Ð°Ñ‚ÐµÐ»Ñ. Задачи, которые решалиÑÑŒ в ходе иÑÑледованиÑ: иÑÑледование Ñтруктуры ÑиÑтемы; коррелÑционный анализ; Ð²Ð°Ð»Ð¸Ð´Ð°Ñ†Ð¸Ñ Ð¸Ñходных данных; обзор видов регреÑÑионного анализа; регреÑÑионный анализ; перÑпективы и Ð½Ð°Ð¿Ñ€Ð°Ð²Ð»ÐµÐ½Ð¸Ñ Ð´Ð°Ð»ÑŒÐ½ÐµÐ¹ÑˆÐ¸Ñ… иÑÑледований. Ð’ результате иÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ Ð±Ñ‹Ð»Ð¸ получены регреÑÑионные формулы пÑти Ñтепеней Ð´Ð»Ñ Ð¿Ð¾Ð´Ð´ÐµÑ€Ð¶Ð°Ð½Ð¸Ñ Ñ‚ÐµÐ¼Ð¿ÐµÑ€Ð°Ñ‚ÑƒÑ€Ñ‹ в транÑпортном трубопроводе. Работа выполнена Ñ Ð¿Ð¾Ð¼Ð¾Ñ‰ÑŒÑŽ программы Ð´Ð»Ñ Ñ€Ð°Ð±Ð¾Ñ‚Ñ‹ Ñ Ñлектронными таблицами Microsoft Excel, Ñзыка Ð¿Ñ€Ð¾Ð³Ñ€Ð°Ð¼Ð¼Ð¸Ñ€Ð¾Ð²Ð°Ð½Ð¸Ñ Python.
This work is devoted to the automation of the process of temperature maintenance in the transportation pipeline based on the derivation of the regression formula for the heater. Tasks that were solved during the study: investigation of the system structure; correlation analysis; validation of the initial data; review of the types of regression analysis; regression analysis; prospects and directions for further research. As a result of the study, five-degree regression formulas for temperature maintenance in the transportation pipeline were derived. The work was performed using Microsoft Excel spreadsheet program, Python programming language.
коÑÑелÑÑиÑ, transportation pipeline, machine learning, correlation, ÑÑанÑпоÑÑнÑй ÑÑÑбопÑовод, маÑинное обÑÑение, regression, ÑегÑеÑÑиÑ
коÑÑелÑÑиÑ, transportation pipeline, machine learning, correlation, ÑÑанÑпоÑÑнÑй ÑÑÑбопÑовод, маÑинное обÑÑение, regression, ÑегÑеÑÑиÑ
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