Prediction of road safety indicators based on statistical analysis

Матросова,; Matrosova, Lidiya; Семенов,; Семенов, Е Ю

doi:10.12737/20384

Central Russian Journal of Social Sciences

2016

DOI: 10.12737/20384

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Prediction of road safety indicators based on statistical analysis

Матросова Матросова¹,

Lidiya Matrosova²,

Семенов Семенов³

et al.

Abstract: The article examines the problems of organization of the comprehensive statistical analysis using automated information systems for processing information of traffic accidents. To solve the problems the Multiparameter information-analytical system (MIAS) of monitoring, analysis and prediction of the situation in the field of road safety was developed. The system allows to estimate thresholds of situation indicators in the field of road safety as a subject of operational and annual information by using methods … Show more

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Analysis and Prediction of CET4 Scores Based on Data Mining Algorithm

Wang

2021

Complexity

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This paper presents the concept and algorithm of data mining and focuses on the linear regression algorithm. Based on the multiple linear regression algorithm, many factors affecting CET4 are analyzed. Ideas based on data mining, collecting history data and appropriate to transform, using statistical analysis techniques to the many factors influencing the CET-4 test were analyzed, and we have obtained the CET-4 test result and its influencing factors. It was found that the linear regression relationship between the degrees of fit was relatively high. We further improve the algorithm and establish a partition-weighted K-nearest neighbor algorithm. The K-weighted K nearest neighbor algorithm and the partition algorithm are used in the CET-4 test score classification prediction, and the statistical method is used to study the relevant factors that affect the CET-4 test score, and screen classification is performed to predict when the comparison verification will pass. The weight K of the input feature and the adjacent feature are weighted, although the allocation algorithm of the adjacent classification effect has not been significantly improved, but the stability classification is better than K-nearest neighbor algorithm, its classification efficiency is greatly improved, classification time is greatly reduced, and classification efficiency is increased by 119%. In order to detect potential risk graduating students earlier, this paper proposes an appropriate and timely early warning and preschool K-nearest neighbor algorithm classification model. Taking test scores or make-up exams and re-learning as input features, the classification model can effectively predict ordinary students who have not graduated.

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Analysis and Prediction of CET4 Scores Based on Data Mining Algorithm

Wang

2021

Complexity

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The system analysis and mathematical modeling road accidents in the metropolis

Давыдовский

Линник

2019

Sist. anal.i prikl. inform.

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The article presents the results of correlation analysis of the causes of road accidents in such a modern metropolis as Minsk. Has been identified the most frequent causes of road accidents, including pedestrian collisions caused by drivers, collisions at intersections, incidents at controlled and unregulated pedestrian crossings, as well as on the roadway. The dependence of transport incidents on the time of day, day of the week and month of the year was investigated. Shows the periods when road traffic incidents occur from 3.00 to 6.00 h, from 15.00 to 18.00 and from 21.00 to 24.00 on Monday, Friday and Sunday in January, March, June, September, October and November. Methods of correlation and multiple regression analysis can be the basis of preventive traffic safety management in a modern metropolis.

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Features of mathematical modeling of road safety on highways

Guseinov,

Dadaeva,

Shabazov

et al. 2024

Vestn. Dagest. gos. teh. univ., Teh. nauki

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Objective. The purpose of the work is to apply mathematical modeling methods to solve problems of ensuring road safety on highways.Method. Quantitative methods for analyzing road safety problems (BDD) are based on probability theory, mathematical statistics, information theory, multifactor analysis, reliability theory, modeling, programming and other mathematical methods.Result. The main trends in the study of road safety problems are considered. It is indicated that the mathematical dependences of the influence of a limited number of factors are unsuitable for a satisfactory description of the “driver-vehicle-road-environment” (VADS) system as a whole. Paying attention to the uncertainty of objects, properties and connections of the VADS system, the need to use a systematic approach in solving these problems is justified. The need to take into account regional conditions in road safety is discussed. Mathematical models recommended for solving problems of ensuring road safety are presented.Conclusion. Generalization, systematization of the vast empirical material of road accidents accumulated as a result of specific studies taking into account economic, social and demographic conditions and the development of theoretical concepts based on system representations are the most important conditions for solving the problems of ensuring road safety.

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Prediction of road safety indicators based on statistical analysis

Cited by 3 publications

References 1 publication

Analysis and Prediction of CET4 Scores Based on Data Mining Algorithm

Analysis and Prediction of CET4 Scores Based on Data Mining Algorithm

The system analysis and mathematical modeling road accidents in the metropolis

Features of mathematical modeling of road safety on highways

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