Scientific Journal of KubSAU

Polythematic online scientific journal
of Kuban State Agrarian University
ISSN 1990-4665
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Name

Medovschikov Maxim Igorevich

Scholastic degree

—

Academic rank

—

Honorary rank

—

Organization, job position

Kuban State Technological University
   

Web site url

http://chemmalion.info/

Email

medovshikov.max@gmail.com


Articles count: 3

803 kb

ACOUSTIC SIGNAL BASED TRAFFIC FLOW EVALUATION METHOD USING THE CALCULUS OF FINITE DIFFERENCES

abstract 0841210076 issue 84 pp. 956 – 966 28.12.2012 ru 1632
In this article, acoustic signal based traffic flow evaluation method using the calculus of finite differences is considered. The analytical survey for traffic flow evaluations using acoustic signals is performed. The calculus of finite differences application in traffic flow evaluation is investigated. As the result of this work, the considered method of efficiency is evaluated
489 kb

HIGH DENSITY TRAFFIC FLOW ADAPTIVE CONTROL METHOD FOR URBAN NETWORKS USING GENETIC ALGORITHM OPTIMIZATION WITH TRAFFIC DYNAMIC MESO-MODEL

abstract 0841210075 issue 84 pp. 945 – 955 28.12.2012 ru 1589
In this article, the high density traffic flow adaptive control method for urban networks is considered. The analytical survey for dynamic traffic models, urban traffic models synthesis, and optimization methods is performed. The genetic algorithm optimization with traffic dynamic meso-model is investigated. As the result of this work, the efficiency indicators of adaptive control are evaluated
186 kb

VEHICLE DETECTION METHOD IN SENSITIVE ZONE OF PASSIVE ACOUSTIC TRANSPORT DETECTOR

abstract 0731109037 issue 73 pp. 395 – 410 30.11.2011 ru 1278
In this article, transport detection method in sensitive zone of passive acoustic transport detector is considered. The transport speed estimation by acoustic data principle is described, an analytical survey for moving object detection is performed, and the mathematical model of described transport detector is investigated. As the result of this work, a transport detection criteria using acoustic data is suggested
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