The Experts below are selected from a list of 321 Experts worldwide ranked by ideXlab platform
F Laue - One of the best experts on this subject based on the ideXlab platform.
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level crossing rate and average duration of fades of deterministic Simulation Models for rice fading channels
IEEE Transactions on Vehicular Technology, 1999Co-Authors: Matthias Patzold, F LaueAbstract:The concept of Rice's sum of sinusoids is often applied to the design of deterministic Simulation Models for Rice fading channels. This paper investigates in detail the level-crossing rate (LCR), average duration of fades (ADF), and cumulative distribution function (CDF) of such classes of Simulation Models. Exact and simple approximative formulas are deduced for these statistical quantities. Several numerical results for the derived expressions are presented by using different procedures for the design of the parameters of the deterministic Simulation model. Moreover, comparisons with the corresponding Simulation results-obtained by evaluating the deterministic Simulation Models output data-are also given.
J.p.c. Kleijnen - One of the best experts on this subject based on the ideXlab platform.
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Statistics and deterministic Simulation Models: why not?
1990 Winter Simulation Conference Proceedings, 1990Co-Authors: J.p.c. KleijnenAbstract:Deterministic Simulation Models are compared with random Simulation Models and real-life experiments. In deterministic Simulation, no mathematical statistics is needed in the experimental design and in the least squares curve fitting. Further analysis, however, becomes possible if certain statistical Models are specified for the fitting errors. Normally identically and independently distributed errors were proposed by the author in 1987. J. Sacks et al. (1989) proposed dependent errors with a specific correlation structure. Needs for further research are indicated.
Matthias Patzold - One of the best experts on this subject based on the ideXlab platform.
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level crossing rate and average duration of fades of deterministic Simulation Models for rice fading channels
IEEE Transactions on Vehicular Technology, 1999Co-Authors: Matthias Patzold, F LaueAbstract:The concept of Rice's sum of sinusoids is often applied to the design of deterministic Simulation Models for Rice fading channels. This paper investigates in detail the level-crossing rate (LCR), average duration of fades (ADF), and cumulative distribution function (CDF) of such classes of Simulation Models. Exact and simple approximative formulas are deduced for these statistical quantities. Several numerical results for the derived expressions are presented by using different procedures for the design of the parameters of the deterministic Simulation model. Moreover, comparisons with the corresponding Simulation results-obtained by evaluating the deterministic Simulation Models output data-are also given.
Gerrit Hoogenboom - One of the best experts on this subject based on the ideXlab platform.
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Assessing crop management options with crop Simulation Models based on generated weather data
Field Crops Research, 2007Co-Authors: Amin Soltani, Gerrit HoogenboomAbstract:The efficient use of crop Simulation Models is an effective complement to experimental research. Long-term weather data obtained at a specific site are normally required for the application of these crop Simulation Models to help determine alternate management practices and associated decisions. Stochastic weather generators sometimes are used to complement or substitute historical weather data. The objective of this study was to evaluate the suitability of weather data generated by the weather generators WGEN and SIMMETEO as input for crop Simulation Models in order to determine the best option(s) among a number of different crop management practices. Five locations across Iran representing different climates were selected. The wheat, maize, and soybean Models of the Decision Support System for Agrotechnology Transfer (DSSAT) were applied in this study, using 30 years of observed weather data and 90 years of weather data generated by WGEN and SIMMETEO. Simulated grain yield using either observed weather data or weather data generated by WGEN and SIMMETEO in response to various 'experimental' factors, e.g., cultivar selection, planting date, planting density, irrigation threshold, and change in precipitation under irrigated and rainfed conditions were compared. The statistical evaluation was based on t, F, and Kolomogrov-Smirnov (K-S) tests. The average of the percentage rejected tests was 20% and the parameter estimation method had no impact on the number of rejected tests. Irrespective of some significant differences between simulated yield based on observed weather data and those based on weather data generated by WGEN and SIMMETEO, a similar conclusion could be drawn about the best cultivar, planting date, plant density and irrigation threshold and response to changes in the amount of precipitation. Based on the results of this study it can be concluded that for many crop model applications where only relative estimates or determination of the best management option(s) rather than absolute values are required, weather data generated by either WGEN and SIMMETEO are accurate and sufficient. © 2007 Elsevier B.V. All rights reserved.
Mario Herrero - One of the best experts on this subject based on the ideXlab platform.
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integrated crop livestock Simulation Models for scenario analysis and impact assessment
Agricultural Systems, 2001Co-Authors: Philip K Thornton, Mario HerreroAbstract:Abstract Despite the fact that many smallholder farming systems in developing countries revolve around the interactions of crop and livestock enterprises, the modelling of these systems using combinations of detailed crop and livestock Models is comparatively under-developed. A wide variety of separate crop and livestock Models exists, but the nature of crop–livestock interactions, and their importance in smallholder farming systems, makes their integration difficult. Even where there is adequate understanding of the biophysical processes involved, integrated crop–livestock Models may be constrained by lack of reliable data for calibration and validation. The construction from scratch of Simulation Models that meet the needs of one particular case is generally too costly to countenance. As for all modelling activity, the most efficient way to proceed depends on the nature of the systems under study and the precise questions that have to be addressed. We outline a framework for the integration of detailed biophysical crop and livestock Simulation Models. We highlight the need for minimum calibration and validation data sets, and conclude by listing various research problems that need attention. The application of robust and trustworthy crop–livestock Models is critical for furthering the research agenda associated with animal agriculture in the tropics and subtropics.
