Pages: 237254
Published: 30.12.2023
Abstract: The zvariabilities of 20 measurements of each of 6 correlated indicators of a grain crop of a supposedly new variety were calculated. The matrix of zvariability values Zm6={zi}, zi =(z1j,z2j,…,zmj)T, j=1,…,6, is transformed into the matrix Ym6=Zm6C66 ={yi}, yj =(y1j,…, ymj)T, uncorrelated yvariability values. 2 matrices (C66,?66) were calculated using the correlation matrix R66, where R66=(1/m)ZTm6Zm6, Ymn=Zm6C66, ?66=(1/m)YTm6Ym6, R66C66=C66?66, C66St66=I66, St66C66=I66, ?66=diag(2.2728,1.9596,0.9124,0.4525,0.3894,0.0132), tr(?66)= ?1+…+?6=6. The initial semantic equality is a semantic matrix equality of the form: meaning (Ym6) = meaning (Zm6C66). A system of 6 semantic equations with 6 unknown ysenses has been developed. The model cognitively models semantic variables and numerically models quantitative relationships between the manifestations of the properties of a grain crop variety.
Key words: semantic variables, matrix semantic equality, mimnogosemantic equation with known and unknown semantic variables, cognitive model of a new variety of grain crop.6 semantic solutions were found: meaning(y1), meaning(y2), meaning(y3),..., meaning(y6), significantly complementing the initial knowledge. We found 6 semantic solutions to the semantic multidimensional equation meaning(y1)(…(meaning(y6)=meaning(Zm6c1)(…( meaning(Zm6c6), where cj=(c1j,c2j…,c6j) T is the jth eigenvector from jth column of the C66 matrix. Implemented in the form of a computer program, formulaic and phraseological types of model elements are given, and visualized on graphs describing the mutual relationships of the manifestations of the properties of a grain crop variety. The semantic and formulaic justification of knowledge from 6 semantic equations is given.The semantic and formulaic justification of knowledge from 6 semantic equations is given. The sequence of extracted knowledge (Table 4) reflects the noticeably strong randomness (of the actual types of work of the breeder) of the fact of manifestations of factors {z1, z5, z6} that made it possible to achieve the desired effect  a noticeably high yield of a new variety of grain crop. The model shows a noticeably strong randomness of the fact of manifestation of factor {z1, z5, z6}, and the breeder “got lucky” as a result of his correctly planned types of work. Key words: semantic variables, matrix semantic equality, mimnogosemantic equation with known and unknown semantic variables, cognitive model of a new variety of grain crop.
