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相关论文: Cellular Models for River Networks

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The effects of erosion, avalanching and random precipitation are captured in a simple stochastic partial differential equation for modelling the evolution of river networks. Our model leads to a self-organized structured landscape and to…

凝聚态物理 · 物理学 2009-10-28 Achille Giacometti , Amos Maritan , Jayanth R. Banavar

Natural rivers connect to each other to form networks. The geometric structure of a river network can significantly influence spatial dynamics of populations in the system. We consider a process-oriented model to describe population…

偏微分方程分析 · 数学 2019-06-26 Yu Jin , Rui Peng , Junping Shi

We analyze the Optimal Channel Network model for river networks using both analytical and numerical approaches. This is a lattice model in which a functional describing the dissipated energy is introduced and minimized in order to find the…

统计力学 · 物理学 2009-10-28 F. Colaiori , A. Flammini , A. Maritan , J. R. Banavar

River networks serve as a paradigmatic example of all branching networks. Essential to understanding the overall structure of river networks is a knowledge of their detailed architecture. Here we show that sub-branches are distributed…

地球物理 · 物理学 2013-05-29 Peter Sheridan Dodds , Daniel H. Rothman

The hierarchy of channel networks in landscapes displays features that are characteristic of non-equilibrium complex systems. Here we show that a sequence of increasingly complex ridge and valley networks is produced by a system of partial…

地球物理 · 物理学 2019-05-09 Sara Bonetti , Milad Hooshyar , Carlo Camporeale , Amilcare Porporato

The existence and stability of the universality class associated to local minimal energy landscapes is investigated. Using extensive numerical simulations, we first study the dependence on a parameter $\gamma$ of a partial differential…

统计力学 · 物理学 2009-10-31 Achille Giacometti

We investigate the dependence of river network scaling on the relative dominance of slope vs. noise in initial conditions, using an erosion model. Increasing slope causes network patterns to transition from dendritic to parallel and results…

地球物理 · 物理学 2009-09-29 Geoffrey M. Poore , Susan W. Kieffer

This article is the first in a series of three papers investigating the detailed geometry of river networks. Large-scale river networks mark an important class of two-dimensional branching networks, being not only of intrinsic interest but…

地球物理 · 物理学 2013-05-29 Peter Sheridan Dodds , Daniel H. Rothman

We present a general model for the growth of weighted networks in which the structural growth is coupled with the edges' weight dynamical evolution. The model is based on a simple weight-driven dynamics and a weights' reinforcement…

统计力学 · 物理学 2009-11-10 Alain Barrat , Marc Barthelemy , Alessandro Vespignani

Large-scale blockages like buildings affect the performance of urban cellular networks, especially at higher frequencies. Unfortunately, such blockage effects are either neglected or characterized by oversimplified models in the analysis of…

信息论 · 计算机科学 2013-09-18 Tianyang Bai , Rahul Vaze , Robert W. Heath

We find that watersheds in real and artificial landscapes can be strongly affected by small, local perturbations like landslides or tectonic motions. We observe power-law scaling behavior for both the distribution of areas enclosed by the…

无序系统与神经网络 · 物理学 2011-02-01 E. Fehr , D. Kadau , J. S. Andrade , H. J. Herrmann

Real networks often grow through the sequential addition of new nodes that connect to older ones in the graph. However, many real systems evolve through the branching of fundamental units, whether those be scientific fields, countries, or…

物理与社会 · 物理学 2020-06-30 Muhua Zheng , Guillermo García-Pérez , Marián Boguñá , M. Ángeles Serrano

We consider a model for the formation of a river network in which erosion process plays a role only at the initial stage. Once a global connectivity is achieved, no further evolution takes place. In spite of this, the network reproduces…

凝聚态物理 · 物理学 2009-10-28 S. S. Manna , B. Subramanian

A new model ecosystem consisting of many interacting species is introduced. The species are connected through a random matrix with a given connectivity. It is shown that the system is organized close to a boundary of marginal stability in…

adap-org · 物理学 2007-05-23 Ricard V. Sole , David Alonso , Alan McKane

What is the best way to divide a rugged landscape? Since ancient times, watersheds separating adjacent water systems that flow, for example, toward different seas, have been used to delimit boundaries. Interestingly, serious and even tense…

地球物理 · 物理学 2014-12-19 N. A. M. Araújo , K. J. Schrenk , H. J. Herrmann , J. S. Andrade

The topology of the network of load transmitting connections plays an essential role in the cascading failure dynamics of complex systems driven by the redistribution of load after local breakdown events. In particular, as the network…

无序系统与神经网络 · 物理学 2023-11-21 G. Pál , Zs. Danku , A. Batool , V. Kádár , N. Yoshioka , N. Ito , G. Ódor , F. Kun

Accurate and scalable hydrologic models are essential building blocks of several important applications, from water resource management to timely flood warnings. However, as the climate changes, precipitation and rainfall-runoff pattern…

机器学习 · 计算机科学 2020-07-02 Zach Moshe , Asher Metzger , Gal Elidan , Frederik Kratzert , Sella Nevo , Ran El-Yaniv

Natural ecosystems are characterized by striking diversity of form and functions and yet exhibit deep symmetries emerging across scales of space, time and organizational complexity. Species-area relationships and species-abundance…

Several cellular activities, such as directed cell migration, are coordinated by an intricate network of biochemical reactions which lead to a polarised state of the cell, in which cellular symmetry is broken, causing the cell to have a…

With the deterioration of climate, the phenomenon of rain-induced flooding has become frequent. To mitigate its impact, recent works adopt convolutional neural network or its variants to predict the floods. However, these methods directly…

计算机视觉与模式识别 · 计算机科学 2023-12-13 Feifei Wang , Yong Wang , Bing Li , Qidong Huang , Shaoqing Chen
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