2,838 research outputs found
Neural network modelling of a boiler combustion system
Boiler combustion systems represent highly nonlinear systems with associated lags and delays
which depend on operating point. Such systems represent a significant challenge to the control
engineer. In this paper, we present a model typical of a medium-size industrial boiler, which
highlights the difficulties associated with such systems. As a starting point for nonlinear control
design, we demonstrate how a neural network may be used to obtain a concise functional
description of the system, initially for fixed operating points and then for variation over the full
range of operation
Random acyclic networks
Directed acyclic graphs are a fundamental class of networks that includes
citation networks, food webs, and family trees, among others. Here we define a
random graph model for directed acyclic graphs and give solutions for a number
of the model's properties, including connection probabilities and component
sizes, as well as a fast algorithm for simulating the model on a computer. We
compare the predictions of the model to a real-world network of citations
between physics papers and find surprisingly good agreement, suggesting that
the structure of the real network may be quite well described by the random
graph.Comment: 4 pages, 2 figure
Localization Transition of Biased Random Walks on Random Networks
We study random walks on large random graphs that are biased towards a
randomly chosen but fixed target node. We show that a critical bias strength
b_c exists such that most walks find the target within a finite time when
b>b_c. For b<b_c, a finite fraction of walks drifts off to infinity before
hitting the target. The phase transition at b=b_c is second order, but finite
size behavior is complex and does not obey the usual finite size scaling
ansatz. By extending rigorous results for biased walks on Galton-Watson trees,
we give the exact analytical value for b_c and verify it by large scale
simulations.Comment: 4 pages, includes 4 figure
Interfaces and the edge percolation map of random directed networks
The traditional node percolation map of directed networks is reanalyzed in
terms of edges. In the percolated phase, edges can mainly organize into five
distinct giant connected components, interfaces bridging the communication of
nodes in the strongly connected component and those in the in- and
out-components. Formal equations for the relative sizes in number of edges of
these giant structures are derived for arbitrary joint degree distributions in
the presence of local and two-point correlations. The uncorrelated null model
is fully solved analytically and compared against simulations, finding an
excellent agreement between the theoretical predictions and the edge
percolation map of synthetically generated networks with exponential or
scale-free in-degree distribution and exponential out-degree distribution.
Interfaces, and their internal organization giving place from "hairy ball"
percolation landscapes to bottleneck straits, could bring new light to the
discussion of how structure is interwoven with functionality, in particular in
flow networks.Comment: 20 pages, 4 figure
The Balkan Aegean migrations revisited: changes in material culture and settlement patterns in the late bronze age central Balkans in light of new data
Alleged “Aegean migrations” have long been seen as underlying major transformations in lifeways and identity in the Balkans in the 12th–11th centuries BC. Revisiting the material culture and settlement changes in the north-south “routeway” of the Velika Morava–Južna Morava–Vardar/Axios river valleys, this paper evaluates developments within local communities. It is argued that mobility played an important role in social change, including an element of inward migration from the north. We argue that rather than an Aegean end point, these river valleys themselves were the destination of migrants. The prosperity this stimulated within those communities led to increased networks of personal mobility that incorporated elements from communities from the wider Carpathians and the north of Greece over the course of two centuries
Properties of Random Graphs with Hidden Color
We investigate in some detail a recently suggested general class of ensembles
of sparse undirected random graphs based on a hidden stub-coloring, with or
without the restriction to nondegenerate graphs. The calculability of local and
global structural properties of graphs from the resulting ensembles is
demonstrated. Cluster size statistics are derived with generating function
techniques, yielding a well-defined percolation threshold. Explicit rules are
derived for the enumeration of small subgraphs. Duality and redundancy is
discussed, and subclasses corresponding to commonly studied models are
identified.Comment: 14 pages, LaTeX, no figure
A dissemination strategy for immunizing scale-free networks
We consider the problem of distributing a vaccine for immunizing a scale-free
network against a given virus or worm. We introduce a new method, based on
vaccine dissemination, that seems to reflect more accurately what is expected
to occur in real-world networks. Also, since the dissemination is performed
using only local information, the method can be easily employed in practice.
Using a random-graph framework, we analyze our method both mathematically and
by means of simulations. We demonstrate its efficacy regarding the trade-off
between the expected number of nodes that receive the vaccine and the network's
resulting vulnerability to develop an epidemic as the virus or worm attempts to
infect one of its nodes. For some scenarios, the new method is seen to render
the network practically invulnerable to attacks while requiring only a small
fraction of the nodes to receive the vaccine
Matchings and loose cycles in the semirandom hypergraph model
We study the 2-offer semirandom 3-uniform hypergraph model on vertices.
At each step, we are presented with 2 uniformly random vertices. We choose any
other vertex, thus creating a hyperedge of size 3. We show a strategy that
constructs a perfect matching, and another that constructs a loose Hamilton
cycle, both succeeding asymptotically almost surely within steps.
Both results extend to -uniform hypergraphs. Much of the analysis is done on
an auxiliary graph that is a uniform -out subgraph of a random bipartite
graph, and this tool may be useful in other contexts
Percolation transition and distribution of connected components in generalized random network ensembles
In this work, we study the percolation transition and large deviation
properties of generalized canonical network ensembles. This new type of random
networks might have a very rich complex structure, including high heterogeneous
degree sequences, non-trivial community structure or specific spatial
dependence of the link probability for networks embedded in a metric space. We
find the cluster distribution of the networks in these ensembles by mapping the
problem to a fully connected Potts model with heterogeneous couplings. We show
that the nature of the Potts model phase transition, linked to the birth of a
giant component, has a crossover from second to first order when the number of
critical colors in all the networks under study. These results shed
light on the properties of dynamical processes defined on these network
ensembles.Comment: 27 pages, 15 figure
Evolution equation for a model of surface relaxation in complex networks
In this paper we derive analytically the evolution equation of the interface
for a model of surface growth with relaxation to the minimum (SRM) in complex
networks. We were inspired by the disagreement between the scaling results of
the steady state of the fluctuations between the discrete SRM model and the
Edward-Wilkinson process found in scale-free networks with degree distribution
for [Pastore y Piontti {\it et al.},
Phys. Rev. E {\bf 76}, 046117 (2007)]. Even though for Euclidean lattices the
evolution equation is linear, we find that in complex heterogeneous networks
non-linear terms appear due to the heterogeneity and the lack of symmetry of
the network; they produce a logarithmic divergency of the saturation roughness
with the system size as found by Pastore y Piontti {\it et al.} for .Comment: 9 pages, 2 figure
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