Spatial simulation is very important study field, by which we can forecast or reproduce a phenomenon in computer.
Storm flow may become to flood when the channels or lakes can't hold the surface water, so it is very useful and
significant to simulate the process of storm flow in computer. In past years, simulation on surface water flow has made a
great progress, and many corresponding simulation models have been produced. However, those models are almost
steady-state model, which just focus on the water flow result rather than process, and also they are always very
complicated, inefficient or inaccurate, when Cellular Automata model has been referred to spatial simulation area, the
simulation becomes easier ,and the simulation models become simple and efficient. Strom flow is one kind of surface
water flow, However it has its own special characteristics. In this paper, a spatial simulation model for storm flow
process based on Cellular Automata is proposed, which is an unsteady-state model (real time dynamic model).Using this
model, we can simulate the entire process of the storm flow in computer rather than just the flow result. At last, for
instance, the storm flow process of a small part of Jinsha river watershed has been simulated by the model. The
simulation results show a good agreement with the fact.
The spatial data in GIS-T database is huge and complicated, discovery knowledge from this database is very
important, region traffic network evaluation is one of the important contents. In this paper the author referred
to an integrated algorithm combined Ant colony algorithm with FCM to cluster the traffic data of 15 regions
of Hubei Province, then used the method of maximizing deviation to arrange the clustering result. From the
result we can evaluate the traffic conditions of the 15 regions.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.