Big data analysis in a geoinformatic problem of short-term traffic flow forecasting based on a k nearest neighbors method

Agafonov, Anton; Yumaganov, Alexander; Myasnikov, Vladislav

doi:10.18287/2412-6179-2018-42-6-1101-1111

Cited by 29 publications

(7 citation statements)

References 34 publications

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“…The crucial objective of this approach is to aid in seeking a solution that determines the most efficient order of supply of each object being regarded. The aim of the task is to cut down the travelled distance or the overall transport costs [45]. This classic heuristic instrument is an unsophisticated method not requiring any intricate computations.…”

Section: Design Of Modelsmentioning

confidence: 99%

Modelling Distribution Routes in City Logistics by Applying Operations Research Methods

Stopka¹

2022

PROMTT

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The article focuses on the up-to-date subject from the practical as well as scientific point of view. It specifically discusses a proposal of an approach concerning transport or distribution problems in the range of city logistics and investigates possibilities to use opted operations research methods in this particular area. Specific suggestions lie first and foremost in using selected tools of operations research (i.e. a set of methods concerning vehicle routing problem) to model multiple variants of distribution paths from a determined hub to multiple spokes in order to minimise the overall travelled distance in an urban area. As far as the very research goes, to define distribution paths to supply multiple logistics objects in the range of city logistics, ensuing methods are step by step used: Clarke-Wright algorithm, Mayer algorithm and the nearest neighbour algorithm. The article consists of a conceptual section, describing the relevant theory as well as data and methods used, the practical part and the section encompassing an assessment of the key findings, along with the discussion. A suitable combination of adequate operations research methods and their application to city logistics issues is where an innovative solution of this research lies.

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Section: Design Of Modelsmentioning

confidence: 99%

Modelling Distribution Routes in City Logistics by Applying Operations Research Methods

Stopka¹

2022

PROMTT

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“…The applicability of these models to transport systems is limited due to the strong correlation of the variables of the regression function. Nonparametric regression, in particular, the k-nearest-neighbor method, was used to solve the prediction problem in the papers [3,4,5]. However, the requirement of a large sample size imposes a restriction on the use of this method in real time.…”

Section: Related Workmentioning

confidence: 99%

Performance comparison of machine learning methods in the bus arrival time prediction problem

Agafonov

Yumaganov

2019

Proceedings of the v International Conference Information Technology and Nanotechnology 2019

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The problem of predicting the movement of public transport is one of the most popular problems in the field of transport planning due to its practical significance. Various parametric and non-parametric models are used to solve this problem. In this paper, heterogeneous information affecting the prediction value is used to predict the arrival time of public transport, and a comparison of the main machine learning algorithms for the public transport arrival time forecasting is given: neural networks, support vector regression. An experimental analysis of the algorithms was carried out on real traffic information about bus routes in Samara, Russia.

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“…Today, Big data can be found in many areas [3,4]. One of the most common ways to get big data is to collect data from sensors and devices.…”

Section: Big Datamentioning

confidence: 99%

Big Data, Internet of Things, Augmented Reality: technology convergence in visualization issues

Smuseva

Rolich

Voskov

et al. 2019

Proceedings of the v International Conference Information Technology and Nanotechnology 2019

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The paper reviews the current situation of the Augmented Reality and Internet of Things markets. The implementing possibilities of AR for Big Data visualization from IoT devices are considered in this paper. The review and the analysis of methods, tools, products and data system of the visualization are presented. The paper provides an overview of the programs and devices of Augmented Reality, and an overview of development environments. The paper presents the existing classifications of computerized data visualization tools and proposes new classification, which takes into account interactive visualization, the purpose of the tool, the type of software product, the availability of ready-made templates, and other characteristics. The article proposes the architecture of the system for collecting data from IoT endpoint devices based on the Heltec modules. Experiments based on the developed experimental stand were carried out with Heltec devices of both versions to determine the number of losses with increasing distance between the sending device and the receiving device. The results of measuring the power consumption of these devices are presented in two modes: in standby mode and when sending a message to the Heltec endpoint device and in standby mode and when receiving a message for the base station. These studies were conducted using various data transfer protocols (LoRa, Wi-Fi and Bluetooth). The paper presents the result of the development of a digital twin of a university building and the development of augmented reality software for receiving data from real-time data collection devices.

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Big data analysis in a geoinformatic problem of short-term traffic flow forecasting based on a k nearest neighbors method

Cited by 29 publications

References 34 publications

Modelling Distribution Routes in City Logistics by Applying Operations Research Methods

Modelling Distribution Routes in City Logistics by Applying Operations Research Methods

Performance comparison of machine learning methods in the bus arrival time prediction problem

Big Data, Internet of Things, Augmented Reality: technology convergence in visualization issues

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