Aleksandr Semenov

ORCID: 0000-0003-3251-0534
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About
Contact & Profiles
Research Areas
  • Economic Development and Regional Competitiveness
  • Transport and Logistics Innovations
  • Ancient and Medieval Archaeology Studies
  • Statistical and numerical algorithms
  • Material Science and Thermodynamics
  • Marine and environmental studies
  • Heat Transfer and Mathematical Modeling
  • Archaeology and ancient environmental studies
  • Economic Systems and Logistics Management
  • Forensic Anthropology and Bioarchaeology Studies

Peoples' Friendship University of Russia
2018-2020

The results of a craniometric study the skull man from destroyed burial on territory ground Upper Volga variant Fatyanovo culture are published. It belongs to long-headed hyperdolichocrane very Caucasoid anthropological type with moderate latitudinal parameters facial structure, characterizing physical appearance population culture. To verify assumption different cultural and chronological affiliation cranium, principal component analysis was carried out. includes individual measurements...

10.14258/tpai(2023)35(3).-07 article EN cc-by Teoriya i praktika arkheologicheskikh issledovaniy 2023-09-01

The article considers the historiographical aspect of study settlements Bronze Age and Early Iron Ages Tuva which can be divided into three stages. initial stage (late 1920s - early 1960s) is associated with works by S.A. Teploukhov L.R. Kyzlasov who discovered first dune sites in basin Upper Yenisei river Northern Tuva. At second (mid-1950s 1980s) excavations began at separate Todzha region on shores lake Azas Toora-Khem (S.I. Vainshtein, M.A. Devlet, S.V. Studzitskaya, Vl.A. Semenov)....

10.14258/msapea.2023.3.07 article EN 2023-01-01

The article considers the issues of optimizing use remote sensing data. Built a mathematical model to describe economic effect It is shown that this incorrect optimisation task. Given numerical method solving problem. Also discusses how optimize organizational structure by using genetic algorithm based on sensing. methods considered allow data in an optimal way. proposed allows various generalizations for optimization decision making presence approach associated with evolutionary programming...

10.1051/itmconf/20181804005 article EN cc-by ITM Web of Conferences 2018-01-01
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