- Rietveld_l 1995 Rietveld Software For Mac Osx
- Rietveld_l 1995 Rietveld Software For Mac Os
- Rietveld_l 1995 Rietveld Software For Mac Download
Rietveld_l 1995 Rietveld Software For Mac Osx
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'Staff publications' is the digital repository of Wageningen University & Research
'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.
Publications authored by the staff of the Research Institutes are available from 1995 onwards.
Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.
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Rietveld 1 Rietveld 2 Mla 21.3 19.2 25.622107 22.6 21.9 00000002. Presentation Summary: Rietveld 1 Rietveld 2 MLA 21.3 19.2 25.622107 22.6 21.9 00000002. Here is my estimate of what a “merge binary” dialog should look like. Fullprof - Software for evaluation of powder and single crystal physics diffraction. Could software perform rietveld and LeBail analysis on physics constant wavelength, energy dispersive software and time of flight physics diffractograms. Has the potential to refine software magnetic structures, physics perform simulated an.
- record nr. 455357
Rietveld_l 1995 Rietveld Software For Mac Os
Record number | 455357 |
---|---|
Title | A fully adaptive forecasting model for short-term drinking water demand |
Author(s) | Bakker, M.; Vreeburg, J.H.G.; Schagen, K.M. van; Rietveld, L.C. |
Source | Environmental Modelling & Software 48 (2013). - ISSN 1364-8152 - p. 141 - 151. |
DOI | https://doi.org/10.1016/j.envsoft.2013.06.012 |
Department(s) | Environmental Technology WIMEK |
Refereed Article in a scientific journal | |
2013 | |
Keyword(s) | distribution network - consumption - prediction - operation - systems |
For the optimal control of a water supply system, a short-term water demand forecast is necessary. We developed a model that forecasts the water demand for the next 48 h with 15-min time steps. The model uses measured water demands and static calendar data as single input. Based on this input, the model fully adaptively derives day factors and daily demand patterns for the seven days of the week, and for a configurable number of deviant day types. Although not using weather data as input, the model is able to identify occasional extra water demand in the evening during fair weather periods, and to adjust the forecast accordingly. The model was tested on datasets containing six years of water demand data in six different areas in the central and Southern part of Netherlands. The areas have all the same moderate weather conditions, and vary in size from very large (950,000 inhabitants) to small (2400 inhabitants). The mean absolute percentage error (MAPE) for the 24-h forecasts varied between 1.44 and 5.12%, and for the 15-min time step forecasts between 3.35 and 10.44%. The model is easy to implement, fully adaptive and accurate, which makes it suitable for application in real time control. (C) 2013 Elsevier Ltd. All rights reserved. | |
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Rietveld_l 1995 Rietveld Software For Mac Download
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