KEYWORDS: Data modeling, Systems modeling, Process modeling, Prototyping, Logic, Databases, Data storage, Human-machine interfaces, Decision support systems, Computer programming
Models are often thought as the abstraction of object, phenomenon, system and process. But the present model base system is good at the abstraction of process which starts from the input data to the results. And it falls short of the model composition. Based on the object-oriented methods, this paper aims to discuss a new application-oriented model base system. The structure of model interface parameter is abstracted into descriptive model (DM) which can be regarded a bridge between different models. Using object-oriented method, a series researches has been made focused on DM, and
establish the application-oriented model-base system. The model working flow and user-oriented model inheritance mechanism were designed for applying and maintaining the model resource easily. A prototype system was designed and developed, and an application demonstration is shown to verify its feasibility.
KEYWORDS: Data modeling, Systems modeling, Mathematical modeling, Cognitive modeling, Decision support systems, Statistical analysis, Statistical modeling, Process modeling, Databases, Data storage
The present object-oriented model representing way have not fully addressed the issues of model inheritance for general
users, increase the difficulty of maintenance and model composition, and make the interrelation among models more
complex. This paper aims to make improvement in model presenting way and put forward a new model-base system
frame, which can implement model inheritance for general users and its data and method are thought separately of as
descriptive model (DM) and operative model (OM). The definition of operative model and descriptive ones, model
representing way, correlation and how to ensure their consistency and inter-dependency were discussed in detail. Based
on the frame, our group developed STA-MMS which can be incorporated into other decision support system (DSS) to
manage models and to help users to build new models by reusing existing model resources in the system without
modifying code. The architecture of STA-MMS system and its essential functions are defined. Procedures for model
generalization, representation and composition are developed according to object-oriented concepts and methods.
Finally, we examine how STA-MMS and its associated procedures and techniques are implemented in a prototype
StaGIS to facilitate the construction, retrieval and execution of analytical models in the statistic analyzing process.
In this paper, we present a new approach to integrate Geographic Information System and remote sensing. Its implementation environment is in Grouping Interpretation System (GrIS). GrIS was developed based on application task requirements, visual interpreting procedure and manner, and multi-technique integration. GrIS can operate in both single-computer mode and multi-computer mode with client/server structure in LAN and WAN environment. This system was designed to function within an integrated Geographic Information System, remote sensing processing and image interpretation function. Moreover, it allows the incorporation of raster format with vector format for image interpretation, automatic and semi-automatic interpretation mode respectively. The integration result of image interpretation into grouping interpretation system (GrIS) is demonstrated. The use of this integration technology and the relevant information from GIS leads to an enhanced information extraction and effective analysis in remote sensing images.
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