Analytical Analogies Calculus

Lyabakh, Nikolay; Gibner, Yakov M.

doi:10.1007/978-3-030-50097-9_61

Cited by 4 publications

(1 citation statement)

References 2 publications

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“…One of the major paths of technical evolution at railway transport is the improvement of marshalling yard operations 1 . Hence marshalling yard monitoring and control systems have always been the aim of many researches and developments 2 . The mainstream in this researches is to digitize information and control streams and to increase the intellectual level of the used subsystems and components.…”

Section: Introductionmentioning

confidence: 99%

Using decision tree-based classification rules to improve land device measurement accuracy at a railway marshaling yard

Panasov,

Tseligorov,

Nechitaylo

2024

Third International Conference on Digital Technologies, Optics, and Materials Science (DTIEE 2024)

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The paper discusses main paths to improve the effectiveness of railway intellectual marshalling yard monitoring and control systems and its land devices. It shows which environment conditions and other factors affect the accuracy of land device measurements particularly park track Occupancy Monitor Block which measures the length of unoccupied track portion. The paper shows that the measurements could be corrected by means of classification algorithms. It is suggested to use hierarchic decision trees as a classification rule. It discusses a method to improve classical decision trees building algorithms based on bootstrap method ideas. The suggested method improves accuracy of built decision trees.

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Section: Introductionmentioning

confidence: 99%

Using decision tree-based classification rules to improve land device measurement accuracy at a railway marshaling yard

Panasov,

Tseligorov,

Nechitaylo

2024

Third International Conference on Digital Technologies, Optics, and Materials Science (DTIEE 2024)

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Simulation Model of Retarder Stopper on the End of Classification Tracks

Kornienko

Olgeizer

Sukhanov

et al. 2022

Lecture Notes in Networks and Systems

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Decision Trees-based Anomaly Detection in Computer Assessment Results

Panasov

Nechitaylo

2021

J. Phys.: Conf. Ser.

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A survey of the current software in the area of computer assessments of students at a university is done. This work shows ways to improve quality of computer assessments and educational management. It suggests options to build a computer system for detecting anomalous assessment results of individual students and entire disciplines. This information could then be used to amend lectures and instructional material or management and better intercommunication to students. This work suggests feature sets for the analysis of student assessment results and demonstrates their availability in the current university software. After surveying known artificial intelligence systems this work proves the choice of decision trees for this problem. It suggests methods and algorithms to improve positive prediction rate of decision trees based on ideas of bootstrap method. A software tool was developed that implements the suggested algorithms.

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Analytical Analogies Calculus

Cited by 4 publications

References 2 publications

Using decision tree-based classification rules to improve land device measurement accuracy at a railway marshaling yard

Using decision tree-based classification rules to improve land device measurement accuracy at a railway marshaling yard

Simulation Model of Retarder Stopper on the End of Classification Tracks

Decision Trees-based Anomaly Detection in Computer Assessment Results

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