2020
DOI: 10.1007/978-3-030-39319-9_34
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Artificial Intelligence: Problems and Prospects of Development

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(2 citation statements)
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“…An example of a matrix of pairwise comparisons [9][10][11] For matrix matching, as already mentioned in [9,10,11], the most accurate way is to find the main eigenvector of the matrix, which after normalization becomes the priority vector. The main eigenvector of a matrix {W 1 ; W 2 ; ...W n } is calculated as follows:…”
Section: Methodsmentioning
confidence: 99%
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“…An example of a matrix of pairwise comparisons [9][10][11] For matrix matching, as already mentioned in [9,10,11], the most accurate way is to find the main eigenvector of the matrix, which after normalization becomes the priority vector. The main eigenvector of a matrix {W 1 ; W 2 ; ...W n } is calculated as follows:…”
Section: Methodsmentioning
confidence: 99%
“…In this case, the expert reconsiders the data used to construct the matrix, or another expert is engaged for evaluation. The above procedure is repeated until the significance of the weights of the competitiveness factors is consistent [9][10][11].…”
Section: Methodsmentioning
confidence: 99%