Abstract
This paper presents a 3D visualization system with artificial neural network algorithm that tracks the motion of particles flowing in the water, where we get a great deal of variable information, and predicts the distribution of particles according to the flowing of water and the pattern of their precipitation. Various particles and their mutual collision influencing the force such as buoyancy force, gravitational force, and the pattern of precipitation are considered in this system and we control it by normalizing momentum equation and sequential equation. Flowing particles whose motion is changed with the environment can be visualized in the system presented here as they are in real water. We can track the motion of the particles efficiently and predict the pattern of the particles as well.
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Shin, BS., Kim, CK., Cha, EY. (2003). Applications of the Ecological Visualization System Using Artificial Neural Network and Mathematical Analysis. In: Gedeon, T.(.D., Fung, L.C.C. (eds) AI 2003: Advances in Artificial Intelligence. AI 2003. Lecture Notes in Computer Science(), vol 2903. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24581-0_88
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DOI: https://doi.org/10.1007/978-3-540-24581-0_88
Publisher Name: Springer, Berlin, Heidelberg
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