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A dynamic model of evaluating differential automatic method for solving plane problems based on BP neural network algorithm

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  • He, Yuan
  • Meng, Zhiyi
  • Xu, Hong
  • Zou, Yue

Abstract

Aiming at solving differential equations of plane problems, the algorithm of difference equation is established, and the corresponding program is compiled on BP neural network. The correctness and practicability of the difference equation algorithm are verified. A dynamic model of the parallel difference equation is constructed according to the characteristics of the parallel structure of BP neural network. By calculating examples, the continuity condition under the condition of modulus abruption is further discussed. The study shows that the two groups of differential equations are used to identify and verify the model, and the energy function satisfies both the linear embedding condition and the correct wiring. Furthermore, BP neural network is used to realize the search and routing of the maximum plane. The results show that difference equation calculations have the ability to help BP networks get rid of local minima and get better results.

Suggested Citation

  • He, Yuan & Meng, Zhiyi & Xu, Hong & Zou, Yue, 2020. "A dynamic model of evaluating differential automatic method for solving plane problems based on BP neural network algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
    • Handle: RePEc:eee:phsmap:v:556:y:2020:i:c:s0378437120304386
    DOI: 10.1016/j.physa.2020.124845
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    References listed on IDEAS

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    1. Jack P. C. Kleijnen, 2015. "Response Surface Methodology," International Series in Operations Research & Management Science, in: Michael C Fu (ed.), Handbook of Simulation Optimization, edition 127, chapter 0, pages 81-104, Springer.
    2. Betiku, Eriola & Okunsolawo, Samuel S. & Ajala, Sheriff O. & Odedele, Olatunde S., 2015. "Performance evaluation of artificial neural network coupled with generic algorithm and response surface methodology in modeling and optimization of biodiesel production process parameters from shea tr," Renewable Energy, Elsevier, vol. 76(C), pages 408-417.
    3. Yu Liu & Hong-Zhong Huang & Dan Ling, 2013. "Reliability prediction for evolutionary product in the conceptual design phase using neural network-based fuzzy synthetic assessment," International Journal of Systems Science, Taylor & Francis Journals, vol. 44(3), pages 545-555.
    4. Xiao-Hong Liu & Mi-Yuan Shan & Li-Hong Zhang, 2016. "Low-carbon supply chain resources allocation based on quantum chaos neural network algorithm and learning effect," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(1), pages 389-409, August.
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