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Procedures for model generalization, representation and decomposition are developed according to object-oriented concepts and methods.
Experimental design procedures for model discrimination and for estimation of precise model parameters are usually treated as independent techniques.
In this article we discuss issues with data availability, calibration of large-scale distributed models, and outline procedures for model calibration and uncertainty analysis.
Under this study design, we developed weighted estimating procedures for model parameters in marginal multiplicative intensity models and for the cumulative baseline hazard function.
The overall analysis includes experimental and mathematical procedures for model calibration and validation to assess the suitability of the HYDRUS-2D model to interpret the hydraulic behaviour of a lab-scale permeable pavement system.
Procedures for model parameter determination and optimisation are described, and demonstrated for the prediction of groundnut (i.e. peanut; Arachis hypogaea L). yields across India for the period 1966 1989.
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Additionally, two numerical procedures for modeling of compaction are described.
The results are quite satisfactory because efficient, faster procedures for modeling and inversion of DFA H/V were developed.
The research validated the effectiveness of such systems and identified some limitations and procedures for modelling and design.
We applied a statistical algorithm, BIOdry, which integrates conventional procedures for modeling patterns between annual diameter increments and drought.
This paper aims at reviewing technologies and procedures for modeling and optimizing the second aforementioned phase: the synthesis reactor.
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