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of the latest data and hence more dependable for decision
makers. 2.5 Decision support subsystem
2.4 Integrated Simulation Modeling System
Isim is an integrated modeling system developed for satisfying
a spectrum of applications based on digital city. It adopts a
component-based modeling approach, and at the same time
designs an extensible plug-in framework for giving support to
different modeling paradigms (see Figure 4). In Isim, models
encapsulated as components are taken as “building blocks”. By
coupling these blocks, coarse-grain models are created and
corresponding components for them are generated
automatically. Three aspects of compatibility are checked when
a coupling process is required, which are temporal
compatibility, spatial compatibility and semantic compatibility,
for the purpose of assuring the technical correctness and the
actual significance of created models. In the system, models are
managed on the basis of their metadata, and are able to be
reused in different grains. Each model accepts two kinds of
inputs: parameter and input variable. The first refers to the
parameters of a model that need be specified only once during
model execution. While the latter need to be set in each
simulation step, and therefore are used to exchange data with
other models.
The system is constructed in client/server architecture and tries
to provide a maximum of simplicity for users. The client is
composed of a complete graphical user interface that enables
modelers to create a model by some operations of dragging and
dropping components represented as icons and to simulate a
model. The server consists of a model base, a metadata base, a
plug-in library, and a series of function modules for sustaining
user access, model management and simulation control. Using
the client, modelers can drive the server remotely to generate or
execute a generic model, and explore data transferred from the
server in multiple manners supported by the client, such as
image, table, statistical figure and report.
The decision support subsystem acts as the control center of the
DSS. It drives the other three systems to produce necessary data,
and integrates them to form a general report for emergency
decision makers, according to prepared emergency processes.
An emergency process prescribes some basic elements and
regulates an operation process for a kind of incidents. Generally,
it answers a series of questions as follows:
What data are needed to support decision makings of these
incidents?
What models are required to support decision makings of
these incidents?
What data are needed by each model?
How are these data obtained?
How is this process executed?
Where are the last results sent?
When an incident happens, emergency managers can activate
the decision support system by inputting incident-related data
and call the decision support subsystem to execute a specific
emergency process by the web interface. After that, three tasks
will be executed sequentially to respond the emergency, which
are data collection, model invocation and results integration
(see Figure 5).
£
Emergency
Manager
\ > < Colled Data > CZ
Invoke Model > CIZ
Integrate
: Results
Spatial Database
Management
System
CyberSIG Service
Bus
Integrated
Simulation
Modeling System
Figure 5. Decision support process overview
Figure 4. Isim overview
In the DSS, all emergency models are created and managed in
Isim. At present, some models on prediction and evaluation of
chemical incidents have been provided, and more emergency
models are planned to develop.
On most occasions, CSB is called by the DSS to obtain
necessary data as the input of specific models for an incident,
which assures more accurate prediction of the evolution and
evaluation of the effects of an incident. The associations
between incidents and emergency models, as well as emergency
models and data, are predefined and recorded in the decision
■ support subsystem.
The first task collects necessary data for decision making
analyses and incident prediction. Generally, in terms of source
and content, these data can be categorized into three groups:
incident-related, surroundings-relevant, and model-suited. The
incident-related data are collected on the incident spot and
inputted by emergency responders, which commonly describe
the incident location, type, scale, risk level, primary effect
region, and some other incident specific characters. The
surroundings-relevant data are acquired from SDMS, and have
same content as that of the fundamental urban spatial dataset
described in section 2.1, but limited boundary. The data
boundary is usually ascertained by the inputted incident type
and effect region. The data that is necessary to model
computations, except for the above two groups, constitute the
model-suited data, for example, meteorology data, demographic
census data. These data are obtained from other organizations
under the support of CSB. The three groups of data are gathered
and shape an incident-centric dataset.
The second task invokes Isim to run specific models that are
defined in the emergency process to predict the evolution of an
incident and evaluate its effects. The values of the parameters
and the input variables of the models are obtained from the
dataset generated by the first task. The results calculated that
generally include the effect areas of an incident and potential