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Predictive Model Control for Photovoltaic Station Maximum Power Point Tracking System
Elzein, Imad A., Petrenko, Y. N.
Predictive Model Control for Photovoltaic Station Maximum Power Point Tracking System
Development of mathematical models and methods for highly accurate prediction of coding segments of eukaryotic DNA
Gaiduk, A. N., Galinskij, V. A., Voloshko, V. A.
Development of mathematical models and methods for highly accurate prediction of coding segments
Application of ATR-FTIR spectrometry for express prediction of the organic matter properties of arable leached chernozem
Okunev R., Smirnova E., Giniyatullin K., Sahabiev I., Gordeeva K.
and models with an acceptable level of prediction. For express prediction the most effective ranges
Development and validation of a model for predicting 18-month mortality in type 2 myocardial infarction
Hoang T.H., Maiskov V.V., Merai I.A., Kobalava Z.D.
, Charlson comorbidity index and were independently associated with 18-month mortality. The model to predict
Machine learning-based strength prediction for refractory high-entropy alloys of the Al-Cr-Nb-Ti-V-Zr system
Klimenko, D., Stepanov, N., Jia Li, Qihong Fang, Zherebtsov, S. V.
The aim of this work was to provide a guidance to the prediction and design of high-entropy alloys
The study and management of reliability parameters for automotive equipment using simulation modeling
Khabibullin R., Makarova I., Belyaev E., Suleimanov I., Pernebekov S., Ussipbayev U., Junusbekov A., Balabekov Z.
of military specialists' training. The solution, in the author's opinion, is in realization of the model
A predictive model for assessing the impact of the COVID-19 pandemic on the economies of some Eastern European Countries
Vasiljeva M.
The paper seeks to develop a predictive model for assessing the impact of the (COVID-19) pandemic
The income prediction module of the retail store's network
Pakhomova, K., Peresunko, P., Videnin, S., Soroka, E.
the best prediction model, which has learned by speci c retail dataset. Notice, the architecture of program
Comparative Analysis of Machine Learning Methods for Prediction of Heart Diseases
Savkin M.O., Lyu D., Zidun M., Stepanyan I.V., Alimbayev Ch.A.
for predicting heart disease using electrocardiography and machine learning algorithms was conducted. In total
Predictive Models for Halogen-bond Basicity of Binding Sites of Polyfunctional Molecules
Glavatskikh M., Madzhidov T., Solov'ev V., Marcou G., Horvath D., Graton J., Le Questel J., Varnek A.
set of 598 organic compounds. Developed models were then challenged to make predictions

Страница 11 из 5344

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