DETERMINATION OF HIDDEN LAWS IN THE SELECTION OF WHEAT VARIETIES USING THE INTERVAL METHOD
Keywords:
divided into intervals, feature, recognize the images, informative feature, generalized estimates, latent feature, feature weight, hidden lawsAbstract
In the article, the ordered values of the quantitative features describing the objects of
samples of soft wheat varieties are divided into intervals based on the compactness check. Also, the
issue of solving the problem of dividing the wheat varieties into intervals based on the compactness
hypothesis was considered.
The aim is to calculate the weights of the features of wheat varieties and to distinguish among
them those with the highest weight. In order to divide features into intervals, a sample of objects
divided into classes was taken and a criterion was used based on intra-class similarity and interclass differences.
The sample formed according to the recommendations of experts was smoothing and latentized.
Weights of features were calculated for each of the resulting samples. As a result, informative features
were identified that significantly contribute to the selection of wheat varieties with high grain quality.
The main idea of the article is to implement new approaches to the seed sector of agriculture
through the use of innovative technologies. The obtained results serve to increase productivity in this
sphere and reduce costs and human labor.
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