The paper presents the technical concepts behind the ENSEMBLE system, the methodology adopted to acquire several model predictions in real-time and to produce the multi-model analysis.
This suggests that in these cases uncertainty quantification might benefit from a multi-model analysis, including both low- and high-complexity models.
All models (including human iPS cells and simple systems like worms and flies) are fraught with limitations, but there is power in multi-model analysis that one might hope would lead to a greater likelihood for translation from basic science findings to clinical practice.
Such multi-disciplinary issues are best expressed by multi-objective optimization or, rather, multi-objective model analysis.
This paper provides a systematic method for model bank selection in multi-linear model analysis for nonlinear systems by presenting a new algorithm which incorporates a nonlinearity measure and a modified gap based metric.
192 samples were analyzed for bulk density, texture, pH, SOC, total N, 13C-SOC, oxalate- and dithionite-extractable Fe and Al, root bio- and necromass, and microbial biomass C. For each sampling depth, a multi-effect model analysis was performed to identify the parameters explaining SOC variability.
Next, mixed-effects, multi-level, generalized linear model analysis was performed, adjusted for (fixed effects) baseline scores for the outcome of interest, age, gender, duration of back pain, time since baseline consultation, and (random effects) cluster, clinician and individual patient.
These challenges are partially addressed by applying the Integrated Assessment Framework IAFF) – an integrated multi-scale modeling, analysis, and data management suite – to address key issues in developing and operating an open-pond microalgae production facility.
Through multi-model regression analysis, optimum model and its parameters can be chosen to predict the production effect.
This study explores short and long-term drivers of alternative decarbonization pathways in four major economies (China, India, Europe and USA), using a multi-model decomposition analysis.
In this study multi-model ensemble analysis of extreme runoff is performed based on eight regional climate models (RCMs) provided by the North American Regional Climate Change Assessment Program (NARCCAP).
