ACS Applied Computer Science

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EVALUATION OF STOCK PRICE PREDICTION BASED ON THE SUPPORT VECTOR

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The study involved a numerical analysis of the water dropping process by fixed-wing aircraft. This method, also known as air attack, is used for aerial firefighting, primarily in green areas such as forests and meadows. The conducted calculations allowed for the analysis of the process over time. The calculations were performed based on a SolidWorks model of the M18B Dromader aircraft. After defining the computational domain and setting the boundary conditions, the simulations were carried out using the ANSYS Fluent software. The resulting water dropping area was used to analyze the intensity of water distribution. The volumetric distribution and airflow velocity distribution were analyzed for specified time steps. The boundary layer where air no longer mixes with water during the final phase of water dropping was also determined. The obtained results provide an important contribution to further analyses aimed at optimizing the water dropping process by fixed-wing aircraft.

  • APA 7th style
Izsák, T., Marák, L., & Ormos, M. (2023). Evaluation of stock price prediction based on the support vector. Applied Computer Science, 19(3), 64-82. https://doi.org/10.35784/acs-2023-25
  • Chicago style
Izsák, Tilla, László Marák, and Mihály Ormos. "Evaluation of stock price prediction based on the support vector." Applied Computer Science 19, no. 3 (2023): 64-82.
  • IEEE style
T. Izsák, L. Marák, and M. Ormos, "Evaluation of stock price prediction based on the support vector," Applied Computer Science, vol. 19, no. 3, pp.64-82, 2023, doi: 10.35784/acs-2023-25.
  • Vancouver style
Izsák T, Marák L, Ormos M. Evaluation of stock price prediction based on the support vector.  Applied Computer Science. 2023;19(3):64-82.