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Many model building methods have been applied for predicting biological activities based on structural similarities, such as neural networks (Burden, 1996), fuzzy adaptive least squares (Moriguchi et al., 1992), inductive logic programming (King and Srinivasan, 1997) and frequency-based fragment weighing schemes (Carhart et al., 1985).
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To reduce fossil fuel based energy consumption in buildings, different methods have been proposed.
The existing Building Information Model (BIM -based decision-support methods have BIM -basedto create alternatives rapidly, evaluate multiple metrics, and visualize alternative plans prior to actual construction; however, those methods have primarily focused on beending design and construsedon.
Various methods have been developed for building species distribution models but it is not well known how these methods perform under various assumptions about the form of the underlying species response.
Numerous methods have been applied to operate buildings more efficiently.
A variety of methods have been successfully applied to the problem of building interoperable software systems.
Although many recognition methods have been developed, the robust recognition of buildings elements has not been achieved yet.
Two major classes of methods have been employed to accomplish the large tree-building task: supertrees and supermatrices.
Building upon previous methods (e.g. transposon display [ 20]), several targeted sequencing methods have been developed over the last years (e.g. [ 21, 22]).
Similar methods have been used for the optimal location of wireless access points inside buildings [20 27].
(Similar methods have been used with oil).
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