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Families’ influence on romantic relationship and its reconstruction

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  • Liu, Yang
  • Gao, Jian
  • Wang, Haiying
  • Semba, Sherehe
  • Gu, Changgui
  • Yang, Huijie

Abstract

Families’ influence on romantic relationship is investigated from theoretical and practical perspectives. Theoretically, an ordinary differential equation based model is proposed to describe the romantic relationship between two partners, where the influence received by each individual from its family is taken into account. The introduction of the families’ opinions lead to rich and interesting structure in the dynamical process. With the decreasing response of a partner to its own family, two bifurcations occur, separating the dynamical behavior into three types, i.e., the transition from damping oscillation to one of four stable states, two of stable states, and limit cycles. These findings are explained with the stability analysis of equilibrium points. Practically, for each individual the opinion from its partner’s family is an interesting but hidden variable. The reservoir computing is adopted to discover the hidden variable from the activities of the individual, its family, and its partner. The model and the discovering method can be extended easily to investigate the relationship between two social groups such as the lateral negotiation, where the two representatives play game under the guidance from their own groups each.

Suggested Citation

  • Liu, Yang & Gao, Jian & Wang, Haiying & Semba, Sherehe & Gu, Changgui & Yang, Huijie, 2022. "Families’ influence on romantic relationship and its reconstruction," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    • Handle: RePEc:eee:chsofr:v:155:y:2022:i:c:s096007792101016x
    DOI: 10.1016/j.chaos.2021.111662
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    References listed on IDEAS

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    1. Chen, Xiaolu & Weng, Tongfeng & Gu, Changgui & Yang, Huijie, 2019. "Synchronizing hyperchaotic subsystems with a single variable: A reservoir computing approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
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    3. F. R. Oliver, 1964. "Methods of Estimating the Logistic Growth Function," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 13(2), pages 57-66, June.
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