Eurasian Journal of Mathematical Theory and Computer Sciences

This article provides more information about neural network technologies and how they are used. The authors provide important information on boosting algorithms, using genetic algorithms, minimum spanning trees, and clustering algorithms. The use of neural networks in the classification of electronic document flow attracts more developers of tools. Neural network mathematical models and their working principles are correctly shown. In particular, the formulas and functions of the input and output mechanics of the neural network are described. This information can be useful for learning and researching neural network technologies.

The article proposes a rationale for the kinematic scheme of the destemmer and boils down to determining the rational rotation speed of the dismembrator and pins, ensuring the destruction of grape bunches and the removal of detached berries without damage. The influence of the number of revolutions of the plate and the angle of inclination of the side wall of the plate, small, large diameters and height of the pins installed on the plate of the rotary-pin installation, as well as the humidity of dried grapes on its performance indicators was also studied.

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.