Abstract
The development of regional urban system still remains one of the main problems during the human race history. There are a lot of problems inside this system like overcrowded cities and decaying countryside. All these situations can be reproduced by modelling them using Cellular Automata (CA) [1, 2, 5]. CA models implement algorithms with simple rules and parameter controls, but the result can be a complex behaviour. A stability of naturally formed self‐organized urban system depends on its critical state parameter τ in the power law log(f(x)) = ‐τlog(x). If the system reaches self‐organized critical (SOC) state then it remains in it for a long time. The CA model URBACAM (URBAnistic Cellular Automata Model) describes the long‐lasting term behaviour and shows that the change in behaviour is sensitive to the urban parameter τ of the power law. Regionines urbanistines sistemos vystymasis išlieka viena iš opiausiu problemu žmonijos istorijoje. Keletas tokiu uždaviniu kaip miestu perpildymas, nykstančios kaimo vietoves ir t.t. gali būti nesunkiai modeliuojami naudojant lasteliu automatus (LA). LA metodas ypatingas tuo, kad realizuoja algoritma paprastu taisykliu bei parametru valdymo pagalba, tačiau rezultate galima gauti sudetinga elgsena. Natūraliai susiformavusiu urbanistiniu sistemu stabilumas priklauso nuo sistemos krizines savirangos būsenos (KSB) parametro τ. Jei sistema pasiekia KSB, tai ji ilga laika išlieka joje. LA modelis URBACAM charakterizuoja ilgalaike elgsena ir parodo, jog modelyje jos kitimus itakoja eksponentinio desnio urbanistinis parametras τ.
Highlights
Urbanization is a social process whereby cities grow and societies become more urban
Urban system is a good example of clustering process: all kinds of cities are situated in space differently and have different amount of population inside
URBAn Cellular Automata Model (URBACAM) is done according to simple rules with an interface of Borland Delphi 6. This notwithstanding cellular automata model can be implemented within different software [1]
Summary
Urbanization is a social process whereby cities grow and societies become more urban. In our model a city is represented as an agglomeration of house cells (H) and we call it cluster. When the behaviour is complex it may take an irreducible amount of computational work to answer any given question about it This is not a sign of model imperfection, R. Our model should simulate any real situation just by changing parameters These parameters for the regional urban system are weights of empty place (E), houses (H), time steps T , initial pattern and grid size. The main goal is to find which parameters are essential in controlling the behaviour of the system This task requires a lot of calculations, so in this paper we will evaluate only parameters that reflex SOC long-lasting stability state. We have to find ruling parameters in our model
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