Евразийский журнал математической теории и компьютерных наук

Ushbu maqolada neyron tarmog‘i texnologiyalari va ularning foydalanish usullari haqida ko‘proq ma’lumot berilgan. Mualliflar algoritmlarni oshirish, genetik algoritmlardan foydalanish, minimal qoplamali daraxtalar va klasterlash algoritmlari haqida muhim ma’lumotlar ko‘rsatadilar. Elektron hujjat oqimini tasniflashda neyron tarmoqlaridan foydalanish vositalarini ishlab chiquvchilarni ko‘proq jalb qiladi. Neyron tarmog‘i matematik modellari va ularning ishlovchi prinsiplari to‘g‘ri ko‘rsatilgan. Ayniqsa, neyron tarmog‘ining kiritish va chiqish mexanikasi bo‘yicha formulalar va funksiyalar tasvirlangan. Ushbu ma’lumotlar neyron tarmoq texnologiyalarini o‘rganish va tadqiq qilish uchun foydali bo‘lishi mumkin.

В статье предложена обоснование кинематической схемы гребнеотделителя сводится к определению рациональной частоты вращения дисмембратора и штифтов, обеспечивающих разрушение гроздей винограда и удаление оторвавшихся ягод без повреждения. А также изучен влияние числа оборотов тарелки и угол наклона боковой стенки тарелки, малого, большого диаметров и высоты штифтов, установленных на тарелке роторно-штифтовой установки, а также влажности сушеного винограда на показатели его работы.

This article discusses the significance and application of clustering analysis in categorizing symptoms and clinical signs in clinical medicine. The authors present findings from studies conducted based on experience, demonstrating the success of clustering methods in diagnosing and treating various conditions. Through an analysis of the effectiveness and prospects of such methods, the article draws conclusions about their significant contribution to modern clinical medicine.

Climate modeling and prediction play a crucial role in understanding and combating the effects of climate change. As the Earth's climate becomes increasingly complex and unpredictable, there is a growing need for advanced tools and technologies to accurately forecast future trends. One such innovative approach is the use of neural networks - a form of artificial intelligence that mimics the human brain's ability to learn and adapt. By harnessing the power of neural networks, researchers and scientists are exploring new possibilities for improving the accuracy and efficiency of climate modeling and prediction. This article will take into account the potential benefits of using neural networks in climate science, highlighting their capabilities, applications, challenges, and future directions.