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adjust the outputs to evaluate the accuracy of a model's estimations. This process can be improved by narrowing down the most influential input parameters using statistical methods such as sensitivity analysis [ 10–12 ]. However, the calibration of

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51 567 577 Lawrence , K.C., Park , B., Windham , W.R. & Mao , C. (2003): Calibration of a push broom hyperspectral imaging

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The object of the examination is a typical office building of the 1990s, owned by a multinational company -Siemens- dedicated to energy awareness. The building also meets the energy efficiency category ‘A’ under the 7/2006 TNM Hungarian regulations concerning the energy performance definition of buildings. However, demand has emerged to implement additional changes to reduce energy usage whilst keeping the current climate comfort or even improving it. International experience forecasts around 30% energy saving potential due to optimization of the building automation and energy management system, and thus the interaction and collaboration between the building geometry, structures and services systems. The project has been built in the IDA ICE complex building energy simulation program. Running a one-year dynamic simulation will provide data that can be compared with the measured data of the actual building, so the model can be adjusted and validated to real data. After the calibration it is now possible to test the ideas under safe conditions, in a virtual surrounding. Once a particular vision of the model is proven to work effectively, it is possible to apply this to the real building control management as well.

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the sensing element as mentioned in P. Morerio, et.al, and G. Kong, [ 6 , 7 ]. As well as in [ 7 ], the camera-world mapping is approximated using a GPS-based learning calibration technique, and a new Wavelet-based model of fire’s frequency signature

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the better result as expected. The square root value of the whole data has taken as validating data. From the 192 available data, 14 data were involved for validation, and the remaining 178 data were used for calibration. These 178 data were separated

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ISO (1990): Water quality — calibration and evaluation of analytical methods and estimation of performance characteristics — Part 1: Statistical evaluation of the linear calibration function . International Standard. No 8466

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. & Davies, T. (2002): A user-friendly guide to multivariate calibration and classification The Cromwell Press Ltd, Trowbridge. Davies T. A user

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the model works in different periods. Therefore, the calibration of the hydrologic model was made in periods 1981–1990, 1991–2000, 2001–2010, 2011–2019 that are different in terms of climate. For further analysis, parameters were chosen from the recent

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References AENOR ( 2005 ): General requirements for the competence of testing and calibration laboratories . EN ISO/IEC 17025

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calibration method for fish freshness assessment: a comparison between standard and passive refrigeration modalities. Fd Bioprocess Technol. , DOI 10.1007/s11947-011-0773-6 Cataudella S

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