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Poster Session 2
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Conceptual Data Modeling for Dynamic Revision of Spatio-Temporal Database
3. Framework for the Estimation of the State of Feature Based On Feo Model.
While an estimation of feature must be done based on our proposed framework in the
previous chapter, conceptual framework, integrating various kinds of estimation methods in
each field, remains to be developed. This is an important future works. We can raise some
effective estimation methods: Temporal, spatial reasoning extracting some meaningful
information with symbolization techniques to the various kinds of knowledge (See, for example,
O.Stock(1997). There was a project which aimed to introduce these reasoning techniques to GIS
in NCGIA in early 1990's (Egenhofer, 1998).). Fuzzy reasoning including its uncertainty (See,
for example, Console (1991)). These reasoning techniques have developed in AI. Or we have
statistical method such as maximum likelihood method estimating probability field so that
observed value is most likely one and carman filter with statistical method every changing
dynamical system. Thus the importance of a common point between reasoning techniques in AI
and statistical estimation is getting higher (Aso etc 1997). And mps analysis handles both
aggregated data and disaggregated data with consistency in traffic field as mentioned in 2.5
(Kobayashi 1986).
4. An Example Application of Feo Model To Urban Traffic and Building Management
In this chapter, we apply our FEO model to the urban traffic and building management as one
of main research field, and consider how observation data and event about feature such as car
and building are explained. But because of the space of this paper the detail of this application
will be referred in our presentation or Sekimoto and Shibasaki (1999).
5. Simulation Calculation about Updating Of Database
In this chapter.5 we demonstrated how the dynamical real world with observational data and
event is put into the database by simulation calculation. Here we used building as simulation
target, but validity of accuracy and assumption of modeling is not enough because this
calculation is only for the simulation of database system. On account of paper space detail
problem setting, formalization and results will be referred in our presentation or Sekimoto and
Shibasaki (1999).
6. Conclusions
In this study we considered more intelligent database which can estimate, reconstruct and
predict the dynamic phenomena in the real world from various data as GIS for next generation,
and this time we proposed FEO model as conceptual representation model. And then we showed
the way of applying to building management as case study. FEO model, thus, under
systematization, gives some viewpoints classifying various kinds of observation data.
Furthermore putting data into database in the forms of feature, event and observation enable us
to arrange the accumulations of existing methods and models not only a wide variety of
observational data.
After this, these steps
- Improvement of FEO model as conceptual model
- Implementation of database system based on FEO model
- Application calculation dealing with some case studies
will be developed getting feedback with each other.
7. References
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