Titlebook: Digital and Information Technologies in Economics and Management; Proceedings of the I Arthur Gibadullin Conference proceedings 2024 The Ed

啤酒

https://doi.org/10.1057/9781137516671lysis processes. This opens up new opportunities for improving pyrolysis and deriving valuable biomass products. Moreover, the results of the study could be used to improve existing pyrolysis plants and to develop new technologies for biomass processing. Further studies are planned to further refine the model and expand its application.

獸皮

農(nóng)學(xué)

細(xì)絲

peptic-ulcer

Simulation of a Tubular Pyrolysis Reactor Using Comsol Multiphysics Software,lysis processes. This opens up new opportunities for improving pyrolysis and deriving valuable biomass products. Moreover, the results of the study could be used to improve existing pyrolysis plants and to develop new technologies for biomass processing. Further studies are planned to further refine the model and expand its application.

危機(jī)

Classification of Building Components Using Artificial Intelligence Based on Meta-Information in BIect in the presence of metadata of classification objects. The study also covers the importance of this method for optimizing processes in the construction industry and improving the quality of projects.

Iatrogenic

2367-3370 China, Bulgaria, Uzbekistan, Oman, and Russia.Discusses theThis book covers the III International Scientific and Practical Conference "Digital and Information Technologies in Economics and Management" (DITEM2023) which was held on November 21–23, 2023..?.?The conference addressed issues of networks

prick-test

Shaping Global Industrial Relationsataset formed from messages from several virtual communities of the VKontakte social network. The resulting classifier demonstrated an accuracy of over 70%. The number of likes normalized by the number of views was used as a popularity metric.

entrance

繁榮地區(qū)

Development of a Probabilistic Model for Predicting Advertising Conversion Using Recurrent Neural Nmeters such as hidden layer size, initial learning rate, and others were carefully tuned to strike a balance between performance and training resources. Model evaluation was conducted using mean absolute error (MAE) and mean squared error (MSE).