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Parametric studies have been carried out to arrive at optimal window size and also the percentage of window overlap.
We also show that the optimal window size is influenced by thermal zone configuration and that there is a need for models in which a difference is made between zones with direct and with non-direct solar gains.
However, we show that the difference in space heating demand with optimal window size and with larger window sizes is small, so it is up to the building owner to decide whether or not he wants larger glazing areas to allow for more daylight.
Moreover, a corresponding new optimal window size and,, is obtained.
Instead, an optimal window size is required for optimal performance.
Given S, there exists an optimal window size W which minimizes the error of the prediction.
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The optimal window sizes of South facing triple windows remarkably depended on the glazing model and window opening strategy used.
In this paper, we solve the problem of selecting optimal window sizes from the perspective of physical database design.
Maximum window sizes from an overheating perspective were identified that are larger than the optimal window sizes for space heating demand.
By using this formula, we propose an algorithm that determines the optimal window sizes for maximizing the performance of entire subsequence matchings.
The expected optimal window sizes depend on both the shape of the target's temporal profile, mainly on the target's peak width, which is inversely proportional to the target's velocity, and on the background scene, i.e., on the presence of clouds and their size and velocity, as stated in section "Window size".
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com