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Секция „Моделиране и оптимизация“

Институт по информационни и комуникационни технологии – БАН

← Назад към Състав Образование и научни степени
  • 2020 – Доктор (Информатика), ИИКТ-БАН. Тема: „Интегриране на хетерогенни данни от разпределени IoT устройства“
  • 2016 – НБУ – София, магистър „Софтуерни технологии в интернет“
Национални научни програми
  • ННП „Сигурност и Отбрана“ ДСД-1/07.07.2022 г. (ННП СиО)
  • ННП „Интелигентно животновъдство“ Д01-62/18.03.2021 (ННП ИНТЕ-ЖИВО)
Публикации
  1. Dineva K., Atanasova T.: Health Status Classification for Cows Using Machine Learning and Data Management on AWS Cloud. Animals, 13, 20, MDPI, 2023, DOI:10.3390/ani13203254. SJR Q1, JCR Q1.
  2. Dineva K., Atanasova T.: Analysis of Dairy Cow Behavioral Patterns Using a Combination of IoT Data And Signal Processing Techniques. SGEM 2023, DOI:10.5593/sgem2023/6.1/s25.14. Scopus.
  3. Dineva K., Atanasova T.: FORECASTING WEEKLY COW MILK PRODUCTION USING A MULTIVARIATE TIME SERIES APPROACH. SGEM 2023, DOI:10.5593/sgem2023V/6.2/s25.29. Scopus.
  4. Dineva K., Atanasova T.: RECOGNISING DAIRY COW’S BEHAVIOUR WITH LSTM MODEL TO IMPROVE FARM MANAGEMENT PRACTICES. SGEM 2023, DOI:10.5593/sgem2023V/6.2/s25.43. Scopus.
  5. Dineva K., Atanasova T.: Modelling and Simulation of Cloud-Based Digital Twins in Smart Farming. SGEM Vienna Green, 2023, DOI:10.5593/sgem2022V/6.2/s25.31. SJR:0.14.
  6. Dineva K., Atanasova T., Balabanov T.: CLOUD DATAFLOW FOR MACHINE LEARNING MODELING ON IOT DATA IN SMART LIVESTOCK FARMING. SGEM 2022, DOI:10.5593/sgem2022/6.1/s25.09. SJR:0.217.
  7. Dineva K., Atanasova T.: Cloud Data-Driven Intelligent Monitoring System for Interactive Smart Farming. Sensors, 22, 17, MDPI, 2022, DOI:10.3390/s22176566. SJR:0.8, JCR-IF:3.847.
  8. Dineva K., Atanasova T., Petrov P., Parvanov D., Mateeva G., Kostadinov G.: Towards CPS/IoT System for Livestock Smart Farm Monitoring. IEEE ICAI, 2021, DOI:10.1109/ICAI52893.2021.9639460.
  9. Dineva K., Atanasova T.: Expandable IoT Architecture for Livestock in Agriculture 5.0. SGEM 2021, DOI:10.5593/sgem2021/6.1/s25.19. SJR:0.22.
  10. Dineva K., Atanasova T.: Design of Scalable IoT Architecture based on AWS for Smart Livestock. Animals, 11, 9, MDPI, 2021, DOI:10.3390/ani11092697. SJR:0.61, JCR-IF:3.231, Q1.
  11. Dineva K., Atanasova T.: Architectural ML Framework for IoT Services Delivery Based on Microservices. DCCN 2020, LNCS 12563, Springer, DOI:10.1007/978-3-030-66471-8_53. SJR:0.427 Q2.
  12. Dineva K., Atanasova T.: Machine Learning Solution for IoT Big Data. SGEM 2020, DOI:10.5593/sgem2020/2.1/s07.027. SJR:0.232 Q4.
  13. Dineva K., Atanasova T.: Systematic Look at Machine Learning Algorithms. SGEM 2020, DOI:10.5593/sgem2020/2.1/s07.041. SJR:0.232 Q4.
  14. Dineva K., Atanasova T.: Methodology for Data Processing in Modular IoT System. DCCN 2019, LNCS 11965, Springer, DOI:10.1007/978-3-030-36614-8_35. SJR:0.427 Q2.
  15. Dineva K., Atanasova T.: Integrated Systems With Embedded Sensors for Digital Agriculture. SGEM 2019. SJR:0.232 Q4.
  16. Dineva K., Atanasova T.: Security in IoT Systems. SGEM 2019, DOI:10.5593/sgem2019/2.1. SJR:0.232 Q4.
  17. Dineva K., Atanasova T.: ICT-based Beekeeping using IoT and Machine Learning. DCCN 2018, CCIS 919, Springer, DOI:10.1007/978-3-319-99447-5. SJR:0.188 Q3.
  18. Dineva K., Atanasova T.: Applying machine learning against beehives dataset. SGEM 2018, DOI:10.5593/sgem2018/6.2. SJR:0.232 Q4.
  19. T.D. Balabanov, I.I. Blagoev, K.I. Dineva: Self Rising Tri Layers MLP for Time Series Forecasting. DCCN 2018, CCIS 919, Springer. SJR:0.17.
  20. Dineva K., Atanasova T.: OSEMN process for working over data acquired by IoT devices mounted in beehives. Current Trends in Natural Sciences, 7, 13, 2018, pp. 47–53.
  21. Dineva K., Atanasova T.: Computer System Using Internet of Things for Monitoring of Bee Hives. SGEM GeoConference, 2017, DOI:10.5593/SGEM_GeoConference. SJR:0.232 Q4.
  22. Dineva K., Atanasova T.: Model of Modular IoT-based Bee-Keeping System. ESM’2017, EUROSIS-ETI. (Scopus).