Open AccessComparative Evaluation of Sequential and Parallel Methods for Identifying Measurements of Nearby Objects
Author(s) -
Hennadii Khudov,
AUTHOR_ID,
Serhii Lohachov,
Dmytro Karlov,
Yuriy Solomonenko,
S. Sukonko,
Sergii Gakhovych,
Borys Holovko
Publication year - 2022
Publication title -
international journal emerging technology and advanced engineering
Language(s) - English
Resource type - Journals
ISSN - 2250-2459
DOI - 10.46338/ijetae0222_08
Subject(s) - identification (biology) , computer science , object (grammar) , set (abstract data type) , observational error , statement (logic) , task (project management) , data mining , pattern recognition (psychology) , algorithm , artificial intelligence , mathematics , statistics , management , botany , political science , law , biology , programming language , economics
The paper proposes the comparative evaluation of sequential and parallel methods for identifying measurements of nearby objects. The problem statement is choosing the method for identifying measurements of nearby objects. The decision rule for identifying the results of radio engineering measurements of the coordinates of objects is obtained. The decision rules for identifying objects by sequential and parallel methods under various conditions are obtained. The cases of absence and presence of false marks from nearby objects are considered. The task of choosing serial or parallel methods for identifying measurements from nearby objects was set. The comparative evaluation of serial and parallel measurement identification methods is provided. As an indicator of the effectiveness of the methods, we chosen the probability of identification error. We estimated the probability of identification error depending on the relative average distance between objects in the absence of false measurements and in their presence. It is determined that the probability of an identification error when using the parallel identification method is less than when using the sequential identification method. This gain increases as the average relative distance between objects decreases. Based on the analysis of methods for identifying measurement results, it was found that the most appropriate identification method is a parallel method for identifying measurement results. The efficiency of the method increases with decreasing relative average distance between objects. Keywords— evaluation, sequential method, parallel Method, identification, measurement, nearby object, hypothesis