[
Abdel-Maboud, F., Tawfik, A., Parusheva, S., Salem, M. (2022). Advances of Machine Learning in Electromyography (EMG) Signal Classification (2021). World Journal of Engineering Research and Technology, 8(2), 00001–65114. https://sdbindex.com/Entry/both/130341.
]Search in Google Scholar
[
Açik, A., Atacan, C. (2022). Estimating the ship traffic in the Istanbul Strait through economic growth of region countries. Business and Management Studies: An International Journal, 10(1), 99–119. DOI: 10.15295/bmij.v10i1.1940.
]Search in Google Scholar
[
Aleksandrova, Y. (2021). Comparing Performance of Machine Learning Algorithms for Default Risk Prediction in Peer to Peer Lending. TEM Journal, 133–143. DOI: 10.18421/tem101-16.
]Search in Google Scholar
[
Aleksandrova, Y. (2021). Predictive Analytics Implementation in the Logistic Industry. Economics and Computer Science, 2, 6–22.
]Search in Google Scholar
[
Alizadeh, D., Alesheikh, A.A., Sharif, M. (2020). Prediction of vessels locations and maritime traffic using similarity measurement of trajectory. Annals of GIS 2020, 27(2), 151–162. DOI: 10.1080/19475683.2020.1840434.
]Search in Google Scholar
[
Anderson, D.R., Sweeney, D.J., Williams, T.A., Camm, J.D., Cochran, J.J., Cengage Learning. (2014). Statistics for Business and Economics. CENGAGE Learning.
]Search in Google Scholar
[
Balliauw, M., Kort, P.M., Zhang, A. (2019). Capacity investment decisions of two competing ports under uncertainty: A strategic real options approach. Transportation Research Part B: Methodological, 122, 249–264.
]Search in Google Scholar
[
Barczak, A. (2018). Models of time series with seasonal fluctuations in the forecasting of passenger traffic in air transport based on the study of Wrocław airport. Research Journal of the University of Gdańsk, 80, 17–25. DOI: 10.26881/etil.2018.80.02.
]Search in Google Scholar
[
Delchev, D., Lazarova, V. (2021). Big Data Analysis Architecture. Economic Alternatives, 2, 315–328. DOI: DOI: 10.37075/EA.2021.2.09.
]Search in Google Scholar
[
Dimitrakiev, D., Dachev, Y., Atanasova, K. (2017). The new sea routes on the world map. Nauchni trudove – Visshe voennomorsko uchilishte N. Y. Vaptsarov, 31, 41–48.
]Search in Google Scholar
[
Country level – gross weight of goods handled in all ports (2022). ec.europa.eu. Retrieved from https://ec.europa.eu/eurostat/databrowser/view/mar_mg_aa_cwh/default/%20table?lang=en (3.02.2023).
]Search in Google Scholar
[
Eick, S.G., Fienberg, S.E. (2002). Visual Scalability. Journal of Computational and Graphical Statistics, 11(1), 22–43. DOI: 10.1198/106186002317375604.
]Search in Google Scholar
[
Erl, T., Khattak, W., Buhler, P. (2016). Big Data Fundamentals: Concepts, Drivers & Techniques (The Pearson Service Technology Series from Thomas Erl) (1st ed.). Pearson.
]Search in Google Scholar
[
Ibabe, A., Rayon, F., Martinez, J.L., Garcia-Vazquez, E. (2020). Environmental DNA from plastic and textile marine litter detects exotic and nuisance species nearby ports. PloS one, 15(6), e0228811.
]Search in Google Scholar
[
Luburić, R., Vučinić, M. (2021). The challenges and opportunities of human resource management in the post-pandemic era. Choveshki resursi i tehnologii & Technologies = HR & Technologies, 1, 26–37.
]Search in Google Scholar
[
Marušić, E., Šoda, J., Krčum, M. (2020). The Three-Parameter Classification Model of Seasonal Fluctuations in the Croatian Nautical Port System. Sustainability, 12(12), 5079. DOI: 10.3390/su12125079.
]Search in Google Scholar
[
Mileva, L. (2020). The Big Data Working Process in Digital Transformation Conditions (Origin, Features And Opportunities). Economic Science, education and the real economy: Development and interactions in the digital age (pp. 639–649). Varna: Publishing house Science and Economics Varna.
]Search in Google Scholar
[
Miryanov, R. (2016). Optimizing the Maritime Shipping Management (2021). Izvestiya Journal of University of Economics – Varna, 1, 62–79.
]Search in Google Scholar
[
Miryanov, R. (2017). Optimization of activities and processes in maritime transport enterprises. Varna: Prof. Tsani Kalyandzhiev Monograph Library.
]Search in Google Scholar
[
Morski transport (2022). Retrieved from https://www.nsi.bg/bg/content/1755/%D0%BC%D0%BE%D1%80%D1%81%D0%BA%D0%B8%D1%82%D1%80%D0%B0%D0%BD%D1%81%D0%BF%D0%BE%D1%80%D1%82.
]Search in Google Scholar
[
Nanda, S., Bagchi, J. (2021). Interdependence of ports and economic development of India.
]Search in Google Scholar
[
Pallant, J. (2020). SPSS Survival Manual: A step by step guide to data analysis using IBM SPSS (7th ed.). Routledge. DOI: 10.4324/9781003117452.
]Search in Google Scholar
[
Paing, W.P., Prabnasak, J. (2019). Determinants of Port Performance – Case Study of Five Major Container Ports in Myanmar. IOP Conference Series: Materials Science and Engineering, IOP Publishing, 1 October. DOI: 10.1088/1757-899x/639/1/012004.
]Search in Google Scholar
[
Radan, F., Fatemi Ghomi, S.M.T., Mirzapour Al-e-hashem, S.M.J., Sammak Jalali, M. (2023). Maritime Inventory Routing Problem Considering Weather Conditions and Tide at Ports. Transportation Research Record, 2677(5), 934–950.
]Search in Google Scholar
[
Rusavska, V., Melikh, T., Melikh, O., Chala, T., Babushko, S., Halytska, M. (2019). Estimation of the Influence of the Seasonality Factor in the Strategic Activity of Tourism and Hospitality Enterprises (2019b). International Journal of Innovative Technology and Exploring Engineering, 9(1), 1686–1691. DOI: 10.35940/ijitee.a4773.119119.
]Search in Google Scholar
[
Seeram, E. (2019). An Overview of Correlational Research. Radiologic technology, 91(2), 176–179.
]Search in Google Scholar
[
Ramona, S.A., Pompiliu, C.M., Stoyanova, M. (2019). Data Mining Algorithms for Knowledge Extraction. Springer Proceedings in Business and Economics. DOI: 10.1007/978-3-030-43449-6_20.
]Search in Google Scholar
[
Stoichev, T., Coelho, J.P., De Diego, A., Valenzuela, M.G.L., Pereira, M.E., de Chanvalon, A.T., Amouroux, D. (2020). Multiple regression analysis to assess the contamination with metals and metalloids in surface sediments (Aveiro Lagoon, Portugal). Marine Pollution Bulletin, 159, 111470.
]Search in Google Scholar
[
Stojanov, M. (2021). Impact of the COVID-19 Pandemic on the Retail Trade in Bulgaria. Dialog, 1, 36–49.
]Search in Google Scholar
[
Takoeva, E.A., Datieva, F.S. (2019). Seasonal Fluctuations of Microcirculation at Medical Students with Successful Adaptation and Desynchronosis. In: International Conference on Health and Well-Being in Modern Society (ICHW 2019)(pp. 237–240). Atlantis Press.
]Search in Google Scholar
[
Todorova, S. (2019). Statistics for Data Analysis Using Microsoft Excel. Izvestia Journal of the Union of scientists – Varna, Economic Sciences series, 8(2), 68–74.
]Search in Google Scholar
[
Toscano, D., Murena, F. (2019). Atmospheric ship emissions in ports: A review. Correlation with data of ship traffic, Atmospheric Environment: X, Elsevier BV, October. DOI: 10.1016/j.aeaoa.2019.100050.
]Search in Google Scholar
[
Yordanova, S., Stefanova, K. (2020). Major Technologies and Practical Aspects of the Digital Transformation of Business in a Big Data Environment. Business Management, 1, 5–21.
]Search in Google Scholar
[
Xu, L., Xie, F., Wang, C. (2022). Passive or proactive capacity sharing? A perspective of cooperation and competition between two regional ports. Maritime Policy & Management, 49(4), 492–509.
]Search in Google Scholar
[
Zhang, M., Zhang, D., Fu, S., Kujala, P., Hirdaris, S. (2022). A predictive analytics method for maritime traffic flow complexity estimation in inland waterways. Reliability Engineering & System Safety, 220, 108317. DOI: 10.1016/j.ress.2021.108317.
]Search in Google Scholar
e 