TY  - CHAP
A1  - Menzel, Karsten
A1  - Garrett, James H.
A1  - Mahdavi, A.
A1  - Ries, R.
T1  - Processing "fuzzy" materials sets for environmental impact analysis of buildings
N2  - Processing technical and environmental data on building materials, components, and systems has become more important during the last few years. Increased sensitivity towards environmental and energy problems has lead to the demand for simulation and evaluation of the long term behavior of buildings. The results of such simulations are expected to enable architects and engineers to develop a broader, interdisciplinary understanding of the impact of their products (buildings) on the environment. However, conducting such evaluations is currently hampered by the lack of comprehensive, up-to-date, and ecologically relevant data on building materials, components, and systems. To address this problem, this paper proposes an approach to deal with the absent or uncertain attributes of building materials, components, and systems. In the past, various information systems have been developed to provide data on a limited set of building materials, including precise values pertaining to some of their characteristics, such as availability, manufacturers, costs, etc. These traditional information systems have difficulty in dealing with uncertain, incomplete and sparse data. However, uncertainty and incompleteness characterize the nature of most of the available and environmentally related characteristics of materials, components, and systems. In this paper, a fuzzy-logic-based augmentation of traditional information systems is proposed towards providing management, utilization and manipulation of incomplete and uncertain data.
KW  - Bauwerk
KW  - Umweltfaktor
KW  - CAD
KW  - Fuzzy-Logik
Y1  - 1997
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20111215-4500
ER  - 
TY  - CHAP
A1  - Garrett, James H.
A1  - Akinci, Burcu
A1  - Wang, Hongjun
T1  - Towards Domain-Oriented Semi-Automated Model Matching for Supporting Data Exchange
N2  - The process of matching data represented in two different data models is a longstanding issue in the exchange of data between different software systems. While the traditional manual matching approach cannot meet today’s demands on data exchange, research shows that a fully automated generic approach for model matching is not likely, and generic semi-automated approaches are not easy to implement. In this paper, we present an approach that focuses on matching data models in a specific domain. The approach combines a basic model matching approach and a version matching approach to deduce new matching rules to enable data transfer between two evolving data models.
KW  - Bauwerk
KW  - Datenmanagement
KW  - Datenaustausch
Y1  - 2004
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20111215-1324
ER  -