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An algorithm generating random graphs with power law degree distributions

Author

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  • Volchenkov, D
  • Blanchard, Ph

Abstract

We propose a simple random process generating various types of random graphs and the scale-free random graphs among others. The model is of a threshold nature and differs from the preferential attachment approach discussed in the literature before.

Suggested Citation

  • Volchenkov, D & Blanchard, Ph, 2002. "An algorithm generating random graphs with power law degree distributions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 315(3), pages 677-690.
    • Handle: RePEc:eee:phsmap:v:315:y:2002:i:3:p:677-690
    DOI: 10.1016/S0378-4371(02)01004-X
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    Cited by:

    1. Aliakbary, Sadegh & Motallebi, Sadegh & Rashidian, Sina & Habibi, Jafar & Movaghar, Ali, 2015. "Noise-tolerant model selection and parameter estimation for complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 100-112.
    2. Attar, Niousha & Aliakbary, Sadegh & Nezhad, Zahra Hosseini, 2020. "Automatic generation of adaptive network models based on similarity to the desired complex network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    3. Claudia Hazard-Valdés & Elizabeth Montero, 2023. "A Heuristic Approach for Determining Efficient Vaccination Plans under a SARS-CoV-2 Epidemic Model," Mathematics, MDPI, vol. 11(4), pages 1-32, February.

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