Dopravní Data Predikce

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Dopravní Data Predikce

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dc.contributor.advisor Hrabec, Dušan
dc.contributor.author Varaksin, Denis
dc.date.accessioned 2019-07-04T09:11:14Z
dc.date.available 2019-07-04T09:11:14Z
dc.date.issued 2018-12-03
dc.identifier Elektronický archiv Knihovny UTB
dc.identifier.uri http://hdl.handle.net/10563/45127
dc.description.abstract Data analysis and data prediction is the field of informatics and mathematics, en-gaged in calculation of algorithms and mathematical models that are able to extract practical data from analyzed data. Data analysis has many aspects and approaches, covers different methods in various fields of science and everyday human life. Data prediction and forecasting has interested people for thousands of years, with the new stage of human civilization development - expenditure of computers and different computing machines, data prediction methods and techniques tremendously change. New field of "Big Data" and machine learning, which research data sets that are too large to deal with by traditional data analysis techniques and applications are expanding. In our days "Big Data" are widely used in areas of internet search, economics, business, urban informatics and etc. The urban informatics is one of the most interesting and applicable fields of "Big Data" usage. This field uses information and data sets in the context of smart cities and urban environments with purpose to make quality of life of pedestrians better and improve urban environment. The aim of this project is to create a model, which would predict behavior of one of the most visible part of every urban area - crossroad. Provided information from traffic light controllers (detectors) on the crossroad at "Makro" Zlin is being registered, stored with equal periods of time and analyzed. Data analysis is implemented through usage of different statistical and computation models in a free and open-source integrated development envi-ronment "RStudio" and spreadsheet program for data storage "Microsoft Excel". The project is aimed to predict traffic data on the crossroad.
dc.format 52
dc.language.iso en
dc.publisher Univerzita Tomáše Bati ve Zlíně
dc.rights Bez omezení
dc.subject Traffic cs
dc.subject data cs
dc.subject prediction cs
dc.subject analysis cs
dc.subject ARIMA cs
dc.subject forecast cs
dc.subject AR cs
dc.subject MA cs
dc.subject Loess cs
dc.subject Crossroad cs
dc.subject Traffic en
dc.subject data en
dc.subject prediction en
dc.subject analysis en
dc.subject ARIMA en
dc.subject forecast en
dc.subject AR en
dc.subject MA en
dc.subject Loess en
dc.subject Crossroad en
dc.title Dopravní Data Predikce
dc.title.alternative Traffic Data Prediction
dc.type diplomová práce cs
dc.contributor.referee Popela, Pavel
dc.date.accepted 2019-06-03
dc.description.abstract-translated Data analysis and data prediction is the field of informatics and mathematics, en-gaged in calculation of algorithms and mathematical models that are able to extract practical data from analyzed data. Data analysis has many aspects and approaches, covers different methods in various fields of science and everyday human life. Data prediction and forecasting has interested people for thousands of years, with the new stage of human civilization development - expenditure of computers and different computing machines, data prediction methods and techniques tremendously change. New field of "Big Data" and machine learning, which research data sets that are too large to deal with by traditional data analysis techniques and applications are expanding. In our days "Big Data" are widely used in areas of internet search, economics, business, urban informatics and etc. The urban informatics is one of the most interesting and applicable fields of "Big Data" usage. This field uses information and data sets in the context of smart cities and urban environments with purpose to make quality of life of pedestrians better and improve urban environment. The aim of this project is to create a model, which would predict behavior of one of the most visible part of every urban area - crossroad. Provided information from traffic light controllers (detectors) on the crossroad at "Makro" Zlin is being registered, stored with equal periods of time and analyzed. Data analysis is implemented through usage of different statistical and computation models in a free and open-source integrated development envi-ronment "RStudio" and spreadsheet program for data storage "Microsoft Excel". The project is aimed to predict traffic data on the crossroad.
dc.description.department Ústav informatiky a umělé inteligence
dc.thesis.degree-discipline Information Technologies cs
dc.thesis.degree-discipline Information Technologies en
dc.thesis.degree-grantor Univerzita Tomáše Bati ve Zlíně. Fakulta aplikované informatiky cs
dc.thesis.degree-grantor Tomas Bata University in Zlín. Faculty of Applied Informatics en
dc.thesis.degree-name Ing.
dc.thesis.degree-program Engineering Informatics cs
dc.thesis.degree-program Engineering Informatics en
dc.identifier.stag 52616
utb.result.grade D
dc.date.submitted 2019-05-17
local.subject big Data cs
local.subject dopravní data cs
local.subject inteligentní měst cs
local.subject křižovatky cs
local.subject transportation data en
local.subject intelligent cities en
local.subject prediction en


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