A5094137610- Topic Modeling
- Spectroscopy and Chemometric Analyses
- Higher Education and Employability
- Statistical and Computational Modeling
- Technology-Enhanced Education Studies
- Smart Agriculture and AI
- Advanced Text Analysis Techniques
- Cognitive Computing and Networks
- Advanced Control Systems Optimization
- Fuzzy Logic and Control Systems
- Problem and Project Based Learning
S.Seifullin Kazakh Agro Technical University
2024
This study investigates the application of different ML methods for predicting pest outbreaks in Kazakhstan grain crops. Comprehensive data spanning from 2005 to 2022, including population metrics, meteorological data, and geographical parameters, were employed train neural network forecasting dynamics Phyllotreta vittula pests Kazakhstan. By evaluating various configurations hyperparameters, this research considers MLP, MT-ANN, LSTM, transformer, SVR. The transformer consistently...
The purpose of the study is to solve an extreme mathematical problem—semantic analysis natural language, which can be used in various fields, including marketing research, online translators, and search engines. When training neural network, data methods based on latent Dirichlet allocation model vector representation words were used. This presents development a neurocomputer system for semantic text Kazakh machine learning use model. In course study, stages considered, regarding recognition...
The study of the subject area and creation a conceptual model are important steps in development any system, as they help to determine requirements, functionality structure well establish common vision project before its implementation. Automation agriculture requires analytical systems predict growth pest populations, which turn involves presentation for system. solution this problem will automate work scientists field calculating predicting number pests grain crops. review existing models...