DETERMINATION OF HIDDEN LAWS IN THE SELECTION OF WHEAT VARIETIES USING THE INTERVAL METHOD UDC 004.657
Abstract
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 inter-class 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.
About the Authors
List of references
Sharma S.N, Sain R.S, Sharma R.K. Genetics of spike length in durum wheat. Euphytica 130: 2003. –PP. 155-161.
[2] Eshboyev E., Shodiyev F., Bozorov A. Berilganlarni qayta ishlash algoritmlarida o‘lchov shkalalari va tanlanma fayllarining o‘rni." //FAN VA JAMIYAT" jurnali. Ajiniyoz nomidagi NDPI. – 2019. – №. 3. – С. 7-10.
Madraximov S. F., Saidov D. Y. Stability of the objects of classes and grouping the features //Проблемы вычислительной и прикладной математики. – 2016. – №. 3. – С. 50-54.
Ignatev N. A., Usmanov R. N., Madraximov Sh. F. Berilganlarning intellektual tahlili. – T.: “MUMTOZ SO‘Z”, 2018, 138 s.
Игнатьев Н.А. Синтез факторов в искусственных нейронных сетях // Вычислительные технологии. – Новосибирск, 2005. – Т.10. №3. – С. 32-38.
Вапник В.Н. Алгоритмы и программы восстановления зависимостей. – М.: Наука, 1984. – 816 с.
Згуральская Е.Н. Алгоритм выбора оптимальных границ интервалов разбиения значений признаков при классификации // Известия Самарского научного центра Российской академии наук. Т.14, №4 (3), 2012. – С.826-829.
Игнатьев Н.А. Вычисление обобщённых показателей и интеллектуальный анализ данных // Автоматика и телемеханика. – 2011. –№ 5. – С.183-190.
Шодиев Ф., Эшбоев Э., Дилмуродов Ш. Интеллектуал тизим ёрдамида дон сифати юқори бўлган буғдой навларини аниқлаш //Инновацион технологиялар. – 2022. – Т. 1. – №. 4. – С. 39-44.
Shodiyev F. Tanlanma obyektlari orasidagi yashirin qonuniyatlarni aniqlash //Digital transformation and artificial intelligence. – 2023. – Т. 1. – №. 3. – С. 94-97.
Шодиев Ф., Эшбоев Е., Суярова А. Прогнозирование устойчивости к болезням высококачественных сортов пшеницы с использованием метода расчета обобщенных оценок //E3S Web of Conferences. – EDP Sciences, 2023. – Т. 401. – С. 04063.
How to Cite
Copyright (c) 2024 INNOVATIVE TECHNOLOGIES
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.