Open AccessA STUDY OF THE PROBABILISTIC STATES OF MACHINETRACTOR AGGREGATES FOR WHEAT CULTIVATION
Author(s) -
Dragomir Dragoev,
Krasimir Krasimir,
Krasimira Georgieva
Publication year - 2018
Publication title -
applied researches in technics, technologies and education
Language(s) - English
Resource type - Journals
eISSN - 1314-8796
pISSN - 1314-8788
DOI - 10.15547/artte.2018.02.001
Subject(s) - aggregate (composite) , probabilistic logic , markov chain , tractor , probability theory , graph , markov process , computer science , probability distribution , reliability (semiconductor) , state (computer science) , mathematics , algorithm , machine learning , engineering , theoretical computer science , artificial intelligence , statistics , power (physics) , materials science , physics , quantum mechanics , automotive engineering , composite material
This paper applies Markov's theory of stochastic processes (Graph theory) to identify theprobability of the machine-tractor aggregate being in each of the machine states adopted by the model. It features a graph of the states of a machine-tractor aggregate (Machine-status) operating in plant growing that allows us to determine the probability of the aggregate being in any of the states considered as basic. It proves that with the increase in the level of reliability of the aggregate, in this case its flawless performance, represented by the non-intermittent operation time indicator (time for trouble-free work), the probability that the aggregate will be in a functional state increases.