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News
August 25, 2026
Scientists Develop Algorithm for More Reliable Processors in Data Centres
Researchers from HSE MIEM and Samara University have developed the LRF-3D algorithm to automatically bypass idle nodes in three-dimensional networks-on-chip. Thanks to its hierarchical architecture, the algorithm outperforms existing solutions in both speed and path accuracy, improving processor reliability for use in data centres, supercomputers, and AI computing. The source code and test results are publicly available.
August 24, 2026
Researchers Develop Method for Direct Generation of Regulatory DNA
Researchers at HSE University have developed a model for generating promoters and enhancers—DNA sequences that regulate gene activity. The model works directly with DNA nucleotides, without first transforming them into a continuous numerical representation. This solution could be useful for applications in synthetic biology and gene therapy. The study results were presented at the ICLR 2026 Workshop ‘Generative AI in Genomics (Gen^2): Barriers and Frontiers.’
August 21, 2026
Social Integration: At the Crossroads of Knowledge and Values
The International Laboratory for Social Integration Research (ILSIR) at HSE University studies the challenges faced by vulnerable groups and explores ways to help them participate fully in everyday life. To develop effective solutions, the laboratory’s researchers combine cutting-edge methods with practical fieldwork. In this interview with the HSE News Service, Laboratory Head Elena Iarskaia-Smirnova discusses the laboratory’s work.

 

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Разработка нового тарифного плана телекоммуникационной компании с учетом предпочтений абонентов и инвесторов

Бизнес-информатика. 2018. Т. 43. № 1. С. 39–49.
Т.К. Богданова, Д.Ю.Неклюдов, О.М. Уварова

The market of telecommunications services is one of the most important and promising sectors of Russian economics, and its development has an essential impact on development strategies of all industries. In recent times, we observe a tendency for the operators’ business to shift from providing communications services to supplying integrated ICT services. A positive trend line of market growth is predicted for the coming five years. However, the problem of keeping and even expanding the subscriber base is an ongoing task of all telecom companies. One of the possible solutions to this problem is developing a rational tariff policy, which may take into consideration not only the interests of the company and its investors, but also the subscribers’ preferences. One of the main components of the tariff policy is developing new tariff plans, which meet the afore-mentioned requirements.

In the paper, a new concept of tariff plan development is proposed. It is based on identifying stable groups of existing tariff plans and subscribers’ preferences that are non-linearly related with tariff plan characteristics. The proposed method is based on the concept of client lifetime value (CLV) that characterizes discounted profit received from a customer during all the time he consumes services from the company. This approach gives us an opportunity to build-up a CLV forming model, relying on subscriber’s consumption of mobile services and price characteristics of tariff plans. This seems quite important in the conditions of volatility of the high tech market and intensive changes in patterns of subscribers’ consumption of services.

Within the proposed concept, an info-logical model for developing and evaluating a new tariff plan is developed. The model is based on the synthesis of neural networks and genetic algorithm. The proposed model allows us to make assessment of combinations of tariff plans’ price characteristics created by telecom company specialists, and to determine an optimal combination representing local or global maximum of CLV in the given time interval. This may be done for each subscriber’s consumption profile and for the given period.

The approach gives us an opportunity to choose a tariff plan (from existing and newly created tariffs) for every subscriber cluster, which satisfies subscribers and investor preferences while providing maximum company profit.

 

Research target: Economics and Management
Priority areas: business informatics
Language: Russian
Full text
DOI
Keywords: моделированиеmodelingкластеризациянейронная сетьгенетический алгоритмтарифный планрынок телекоммуникационных услугтарифная политикаclusteringtariff policyтелекоммуникационная компанияgenetic algorithmclient life-time valueпредпочтения абонентовпрофиль абонентского потреблениядолгосрочная ценность клиентаинтеллектуальные методы анализа данныхNeural Networktelecommunications companytelecommunications service markettariff plansubscribers’ preferencessubscriber consumption profileintelligent methods of data analysis
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