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Journal of Applied Mathematics and Computation


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Numerical Algorithm for Transportation Network

Jeffrey Liang

Shanghai Jiao Tong university (SJTU), Shanghai, China.

*Corresponding author: Jeffrey Liang

Date: July 31,2023 Hits: 330


We use the principle of minimum energy to get the differential equation we need. Construct a new algorithm with negative gradient flow to get the final result. Finally, through the method of cross-validation, we can compare the efficiency and complexity of each algorithm. For a long time, we have wondered whether the wings of drones could maintain strength while having little mass. Now we have found a possible solution. If we make the structure of an airplane wing like a dragonfly's wing, we can make the wing strong enough while keeping it light. Because the skeleton of the dragonfly's wings is very supervised, but the membrane is very light and thin, which allows the dragonfly to easily control its posture during flight. The global optimal solution and local optimal solution of optimization problems sometimes make us very contradictory. In order to find the global optimal solution, we have to consume too much time. But if we only spend a short time finding the local optimal solution, we cannot know what the global optimal solution looks like. In our article, we use the method of negative gradient flow, which will help us save time while being able to find the optimal solution.


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Numerical Algorithm for Transportation Network

How to cite this paper: Jeffrey Liang. (2023) Numerical Algorithm for Transportation Network. Journal of Applied Mathematics and Computation7(2), 317-323.

DOI: http://dx.doi.org/10.26855/jamc.2023.06.014