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
Authors:C.O. Amaro, C. Flores, M.G. Dias, and F.C. Lidon
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
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.
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
Authors:A. Păucean, D.C. Vodnar, V. Mureșan, F. Fetea, F. Ranga, S.M. Man, S. Muste, and C. Socaciu
, F. , He , Y. , Wang , L. & Sun , G. ( 2011 ): Detection of organic acids and pH of fruit vinegars using near-infrared spectroscopy and multivariate calibration . Food Bioprocess Tech. , 4 , 1331 – 1340
Calibration of a catchment-based land surface model in the Loire River basin (France) to assess hydrological impacts of climate change, Master Thesis , Environmental Engineering, Technische Universitat Munchen , 2009 .