Hierarchical model evaluation

A Bayesian hierarchical modeling framework was used to evaluate the effects data for each species and test endpoint (Figure 7.4). Hierarchical models reduce the effect of incomplete data sets, small numbers of tests, inconsistent information on effects among species, and other issues that lend uncertainty to the risk characterization results. 

Few papers have been published that apply the PPC to PM modeling (9-11,32). In a limited evaluation of PPC, the authors concluded that the failure of the PPC to invalidate a model offers little assurance that the model is correct (32). Further evaluation of the utihty of the PPC, especially in hierarchical models, is needed. 

Redncr et al. (1987) evaluated pure mechanical dispersion (no diffusion) in a self-similar hierarchical model of a porous medium. They expected their model... 

Establish a hierarchical model of evaluation system for rock burst hazards. For the problems concerning multivariate hierarchical analysis and evaluation on rock burst hazard, divide them into 5 levels, i.e., mining depth, coal structure, geological structure, spatial structure of overlying strata and that induced by coal pillar. Different properties are channeled to different groups at different levels, as shown in Fig. 2, and determine the... 

The coupled hierarchical model was evaluated by comparison with experimental data of Suzuki et al. (2011) and Soboleva et al. (2011). Both of these studies provided experimental data on CL structure as well as electrochemical performance, which were used to parameterize the model. The pore size distributions of the catalyst layers are depicted in Figure 3.42. Figure 4.12a shows polarization curves from both experimental studies compared to the curves obtained from the hierarchical model. Experimental trends are reproduced within the model. It is evident that flooding of the GDL is responsible for the knee in fuel cell voltage at high current density. 

This paper suggests an evaluation of an airport security system based on a hierarchical model of fuzzy reasoning. This approach results from the fact that the tested system is heavily influenced by the human factor and other elements, which are not subject to unequivocal and precise description. It is impossible to detect the functional relationships between the various factors which influence the effectiveness of the security system and an evaluation of the security level. In such cases it is required to use expert opinions. As we have to deal with expert opinions, it is a known fact that very often they are formulated in a descriptive and an imprecise way. We must therefore view the decision making problem in context of uncertainty related to decision making (Dubois Prade 1992). All this locates the decision making problem in an area described by e.g. the theory of fuzzy sets or rough sets (Greco et al. 2001). 

A hierarchical design procedure for process synthesis can be used in conjunction with a flow-sheeting program to analyze, evaluate, and optimize the options (60). The emphasis is on starting with the simplest possible models that will give answers to a particular question quickly so that the questions to be asked at the next decision level can be formulated. At each stage, it is necessary to ensure that the level of detail in the model is sufficient to give rehable information. 

Buehler et al. presented a preliminary study on formation of water from molecular oxygen and hydrogen using a series of atomistic simulations based on ReaxFF MD method.111 They described the dynamics of water formation at a Pt catalyst. By performing this series of studies, we obtain statistically meaningful trajectories that permit to derive the reaction rate constants of water formation. However, the method requires calibrations with either ab initio simulation results in order to correctly evaluate the energetics of OER on Pt. Thus, this method is system specific and less reliable than the ab initio methods and will not replace ab initio methods. Nevertheless, this work demonstrates that atomistic simulation to continuum description can be linked with the ReaxFF MD in a hierarchical multiscale model. 

Current generally applicable biodegradation models focus on the estimation of readily and nonreadily biodegradability in screening tests. This is because most experimental data are from such tests (e.g., MITI-I). There are far fewer data that are both quantitative and environmentally relevant (i.e., measured half-lives or rate constants). However, individual transformations and pathways are well documented in the literature. This allows for development of explicitly mechanistic models, making use of established group-contribution approaches, hierarchic rule-based expert systems, and probabilistic evaluation of possible transformation pathways. 

There is now a growing appreciation for a new model of the world, one "that is hierarchically layered into quasi-autonomous domains, with the ontology and dynamics of each layer essentially quasi-stable and virtually immune to whatever happens in other layers" (Schweber, 1997, p. 172). To evaluate such a model, one wants to know how the sedimentation of these layers takes place and how their boundaries are maintained. How porous are those boundaries, and what types of exchange take place through them As a test case for the assessment of this new vision, chemistry should be an area of continuing interest for the philosophical community. 

M. Zacharias and H. Sklenar, Conformational analysis of single-base bulges in 4-form DNA and RNA using a hierarchical approach and energetic evaluation with a continuum solvent model, J. Mol. Biol. 289, 261-275 (1999). 

Ogunnaike, B., W. H. Ray, 1998, Modelling and Process Control, Academic Press Ponton, J. W., D. M. Liang, 1993, Hierarchical approach to the design of process control system, Chem. Eng. Res. Des., 70, 181 Seider, W. D., J. D. Seader, D. R. Lewin, 1999, Process Design Principles Synthesis, Analysis and Evaluation, Wiley... 

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