Spatial distribution pattern is an arrangement of two or more spatial objects according to some spatial relations, such as
spatial direction, topological and distance relations. In the real world, spatial objects and spatial distribution pattern all
vary continuously along the time-line. Traditional spatial and non-spatial data dissevers this continuous spatio-temporal
process. Under analyzing relations among spatial object, its attributes and spatial distribution pattern, we brought metaspatio-
temporal process, spatio-temporal process and spatial distribution pattern spatio-temporal process. Rainfall in
Eastern China has a typical spatial distribution pattern, being composed of the northern rain area and the southern rain
area. Through constructing spatio-temporal process transactions, the association rules can be extracted from spatiotemporal
process data set by the Apriori algorithm. The result of the spaio-temporal process association rule mining is
consistent with the analysis of the theory. Finally, it is concluded that the spatio-temporal process can describe change of
a spatial object in a defined time range, and change trend of one entity can be forecasted through varying trend of others
based on the valuable spatio-temporal process association rules.
With quick development of economy, spatial distribution and specialization level of China large scale commodity exchange markets whose turnover are more than 100 million Yuan, have changed greatly. And influencing factors which distribute in the research region have attribute information and spatial information and do not satisfy statistical independence. Commodity exchange market specialization index is brought forward to measure specialization degree, based on the former research and constrained co-local spatial association rule is used to analyze symbiotic pattern between specialization level and influencing factors. Constrained predicate templates and association rule templates can improve mining efficiency greatly. As the result shown, large scale commodity exchange market specialization level on
country-region spatial scale went down from 2000 to 2005 and rose at 2006. The interesting association rules extracted based on defined minimum support and confident can provide officers of region governments with rational advices on large scale commodity exchange markets planning and construction.
The objective of this study is to present a novel model for simulating the evolution of gradual change systems. The
proposed model, named SDCA-state delay cellar automata, extends the traditional cellar automata (CA) to include state
delay, variable time step, and state-delay cell evolving to aid prediction making for the gradual systems developments.
The model can perform microcosmic changing happens in one time step through changing state-delay time. In this
article, the SDCA model used to simulate the forest fire spreading which is a typical gradual changing system under
different external conditions. As experiments' result shown, SDCA model can simulate the forest fire spreading and
perform gradual changing with time step varied accurately and simply. Finally, it is concluded that the SDCA model is
an effective model in simulating the gradual changing systems' propagation.