Karst networks from an optimizing neuronal branching model


  • Ricarido M. Saturay, Jr. Philippine Science High School – Cordillera Administrative Region Campus
  • Noelynna T. Ramos National Institute of Geological Sciences, University of the Philippines Diliman
  • Johnrob Y. Bantang National Institute of Physics, University of the Philippines Diliman


A neuronal branching model, optimizing material cost and conduction time based on a balancing factor, was used to generate model karst networks with a branchwork structure. Network properties of the model are compared with those of actual karst networks. Geometric properties include total network length, entropy of orientation, mean branch length, entropy of branch length, coefficient of variation of branch length, and mean tortuosity. Topologic properties include seed node fraction, edge density, average vertex degree, coefficient of variation of degrees, correlation of vertex degrees, average shortest path length, and central point dominance. Effects of the balancing factor on the above properties are discussed. We found correspondence between model and actual networks, mostly in terms of the topologic properties. Further investigations should consider the effects of spatial dimensions, structure, and node distributions on the model karst networks.



Article ID



Earth Systems Physics



How to Cite

RM Saturay, NT Ramos, and JY Bantang, Karst networks from an optimizing neuronal branching model, Proceedings of the Samahang Pisika ng Pilipinas 41, SPP-2023-3D-05 (2023). URL: https://proceedings.spp-online.org/article/view/SPP-2023-3D-05.