Artificial Intelligence (AI) is a rapidly developing field of research that attracts significant funding from both the state and industry players. Such interest is driven by a wide range of AI technology applications in many fields. Since many AI research topics relate to computer science, where a significant share of research results are published in conference proceedings, the same applies to AI. The world leaders in artificial intelligence research are China and the United States. The authors conducted a comparative analysis of the bibliometric indicators of AI conference papers from these two countries based on Scopus data. The analysis aimed to identify conferences that receive above-average citation rates and suggest publication strategies for authors from these countries to participate in conferences that are likely to provide better dissemination of their research results. The results showed that, although Chinese researchers publish more AI papers than those from the United States, US conference papers are cited more frequently. The authors also conducted a correlation analysis of the MNCS index, which revealed no high correlation between MNCS USA vs. MNCS China, MNCS China/MNCS USA vs. MSAR, and MNCS China/MNCS USA vs. CORE ranking indicators.

A queuing system (QS) with several parallel devices and a common storage of limited capacity is considered. The system receives a Poisson flow of requests. A request, that finds all the places in the drive occupied, is lost and does not affect the functioning of the system in the future. The duration of the request service is random, independent of each other and has an exponential distribution. The intensity of maintenance of the devices is different. The request, which has the possibility of selecting a device, selects from all the available devices the one, that has the highest intensity. The functioning of the system is subject to the requirement to maintain the order of withdrawal of requests from it in accordance with their order of receipt. Requests that have violated the order, until it is restored, are contained in the reordering buffer located at the exit of the system. Such QS are known in the literature as systems with reordering of requests [1]–[6]. In [5], an algorithm was developed for calculating the stationary probabilities of the states of the system under consideration. The main task of this work is to obtain analytical expressions for a number of stationary characteristics based on the results of [5].

The article presents the results of the evaluation of quartiles of scientific conferences presented by leading rating agencies. The estimates are based on the use of three methods of multivariate statistical analysis: linear regression, discriminant analysis and neural networks. A training sample was used for evaluation, including the following factors: age and frequency of the conference, number of participants and number of reports, publication activity of the conference organizers, citation of reports. As a result of the study, the linear regression model confirmed the correctness of the quartiles exposed for 77% of conferences, while the methods of neural networks and discriminant analysis gave similar results, confirming the correctness of the quartiles exposed for 81 and 85% of conferences, respectively.