19,881 research outputs found
Fractal Systems of Central Places Based on Intermittency of Space-filling
The central place models are fundamentally important in theoretical geography
and city planning theory. The texture and structure of central place networks
have been demonstrated to be self-similar in both theoretical and empirical
studies. However, the underlying rationale of central place fractals in the
real world has not yet been revealed so far. This paper is devoted to
illustrating the mechanisms by which the fractal patterns can be generated from
central place systems. The structural dimension of the traditional central
place models is d=2 indicating no intermittency in the spatial distribution of
human settlements. This dimension value is inconsistent with empirical
observations. Substituting the complete space filling with the incomplete space
filling, we can obtain central place models with fractional dimension D<d=2
indicative of spatial intermittency. Thus the conventional central place models
are converted into fractal central place models. If we further integrate the
chance factors into the improved central place fractals, the theory will be
able to well explain the real patterns of urban places. As empirical analyses,
the US cities and towns are employed to verify the fractal-based models of
central places.Comment: 30 pages, 8 figures, 5 table
Integrated urban evolutionary modeling
Cellular automata models have proved rather popular as frameworks for simulating the physical growth of cities. Yet their brief history has been marked by a lack of application to real policy contexts, notwithstanding their obvious relevance to topical problems such as urban sprawl. Traditional urban models which emphasize transportation and demography continue to prevail despite their limitations in simulating realistic urban dynamics. To make progress, it is necessary to link CA models to these more traditional forms, focusing on the explicit simulation of the socio-economic attributes of land use activities as well as spatial interaction. There are several ways of tackling this but all are based on integration using various forms of strong and loose coupling which enable generically different models to be connected. Such integration covers many different features of urban simulation from data and software integration to internet operation, from interposing demand with the supply of urban land to enabling growth, location, and distributive mechanisms within such models to be reconciled. Here we will focus on developin
Exact reconciliation of undated trees
Reconciliation methods aim at recovering macro evolutionary events and at
localizing them in the species history, by observing discrepancies between gene
family trees and species trees. In this article we introduce an Integer Linear
Programming (ILP) approach for the NP-hard problem of computing a most
parsimonious time-consistent reconciliation of a gene tree with a species tree
when dating information on speciations is not available. The ILP formulation,
which builds upon the DTL model, returns a most parsimonious reconciliation
ranging over all possible datings of the nodes of the species tree. By studying
its performance on plausible simulated data we conclude that the ILP approach
is significantly faster than a brute force search through the space of all
possible species tree datings. Although the ILP formulation is currently
limited to small trees, we believe that it is an important proof-of-concept
which opens the door to the possibility of developing an exact, parsimony based
approach to dating species trees. The software (ILPEACE) is freely available
for download
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