scholarly journals Erratum: “Growth diffusion-limited aggregation for basin fractal river network evolution model” [AIP Adv. 10, 075317 (2020)]

AIP Advances ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 099901
Author(s):  
Shengwei Wang ◽  
Hao Ji ◽  
Ping Li ◽  
Honghong Li ◽  
Yulin Zhan
Keyword(s):  
Network Evolution ◽  
River Network ◽  
Evolution Model ◽  
Diffusion Limited Aggregation ◽  
Diffusion Limited ◽  
Growth Diffusion

scholarly journals Growth diffusion-limited aggregation for basin fractal river network evolution model

AIP Advances ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 075317 ◽  
Author(s):  
Shengwei Wang ◽  
Hao Ji ◽  
Ping Li ◽  
Honghong Li ◽  
Yulin Zhan
Keyword(s):  
Network Evolution ◽  
River Network ◽  
Evolution Model ◽  
Diffusion Limited Aggregation ◽  
Diffusion Limited ◽  
Growth Diffusion

Anisotropy and Cluster Growth by Diffusion-Limited Aggregation

1985 ◽  
Vol 55 (13) ◽  
pp. 1406-1409 ◽  
Author(s):  
Robin C. Ball ◽  
Robert M. Brady ◽  
Giuseppe Rossi ◽  
Bernard R. Thompson
Keyword(s):  
Cluster Growth ◽  
Diffusion Limited Aggregation ◽  
Diffusion Limited

scholarly journals Dynamic Evolution Model of a Collaborative Innovation Network from the Resource Perspective and an Application Considering Different Government Behaviors

Information ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 138 ◽  
Author(s):  
Wu ◽  
Shao ◽  
Feng
Keyword(s):  
Network Evolution ◽  
Evolution Model ◽  
Dynamic Evolution ◽  
Innovation Network ◽  
Transfer Policy ◽  
Collaborative Innovation ◽  
Innovation Output ◽  
The Government ◽  
Small Change ◽  
Innovative Behaviors

The evolution of a collaborative innovation network depends on the interrelationships among the innovation subjects. Every single small change affects the network topology, which leads to different evolution results. A logical relationship exists between network evolution and innovative behaviors. An accurate understanding of the characteristics of the network structure can help the innovative subjects to adopt appropriate innovative behaviors. This paper summarizes the three characteristics of collaborative innovation networks, knowledge transfer, policy environment, and periodic cooperation, and it establishes a dynamic evolution model for a resource-priority connection mechanism based on innovation resource theory. The network subjects are not randomly testing all of the potential partners, but have a strong tendency to, which is, innovation resource. The evolution process of a collaborative innovation network is simulated with three different government behaviors as experimental objects. The evolution results show that the government should adopt the policy of supporting the enterprises that recently entered the network, which can maintain the innovation vitality of the network and benefit the innovation output. The results of this study also provide a reference for decision-making by the government and enterprises.

Deterministic Growth of Diffusion-Limited Aggregation with Quenched Disorder

1990 ◽  
Vol 13 (4) ◽  
pp. 341-347 ◽  
Author(s):  
A Hansen ◽  
E. L Hinrichsen ◽  
S Roux ◽  
H. J Herrmann ◽  
L. de Arcangelis
Keyword(s):  
Quenched Disorder ◽  
Diffusion Limited Aggregation ◽  
Diffusion Limited

Multifractal spectrum of off-lattice three-dimensional diffusion-limited aggregation

1992 ◽  
Vol 46 (6) ◽  
pp. R3016-R3019 ◽  
Author(s):  
Stefan Schwarzer ◽  
Marek Wolf ◽  
Shlomo Havlin ◽  
Paul Meakin ◽  
H. Eugene Stanley
Keyword(s):  
Three Dimensional ◽  
Multifractal Spectrum ◽  
Diffusion Limited Aggregation ◽  
Diffusion Limited ◽  
Dimensional Diffusion

Thermodynamic and scaling behaviour in finite diffusion-limited aggregation

1992 ◽  
Vol 77 (5) ◽  
pp. 857-867 ◽  
Author(s):  
M. Arturo López-Quintela ◽  
M. Carmen Buján-Núñez
Keyword(s):  
Diffusion Limited Aggregation ◽  
Scaling Behaviour ◽  
Diffusion Limited

Diffusion-limited aggregation as a deterministic growth process

1985 ◽  
Vol 32 (5) ◽  
pp. 3160-3163 ◽  
Author(s):  
L. M. Sander ◽  
P. Ramanlal ◽  
E. Ben-Jacob
Keyword(s):  
Growth Process ◽  
Diffusion Limited Aggregation ◽  
Diffusion Limited

A continuous-time network evolution model describing 3-interactions

2021 ◽  
pp. 1-20
Author(s):  
István Fazekas ◽  
Attila Barta ◽  
Csaba Noszály ◽  
Bettina Porvázsnyik
Keyword(s):  
Continuous Time ◽  
Network Evolution ◽  
Evolution Model
Sign in / Sign up

Export Citation Format

Share Document