Sentences with phrase «nonlinear models in»

Overall, ANN models and tree ensembles outscored the linear models and simple nonlinear models in terms of precipitation occurrences, without performance deteriorating in future climate.

Not exact matches

«Nobody understands anything about «endpoints in carcinogenesis» or «nonlinear models» for disease,» said one frustrated staffer.

In fact, much mainstream economic modelling has already moved into a nonlinear world.

ARL created a generalized model using an energetic formulation approach, which was key in identifying two important mechanisms for enabling high bending motion in soft biological actuators: (i) tuning physical properties (mechanical and geometric) via exploiting the interplay between the materials and dynamic nonlinearities to augment the motion; and (ii) highlighting the electromechanical coupling between the electrical field and nonlinear structural stiffness through the distributive actuation circuitries.

Avadh Saxena has shown how materials modeling methods can be used to answer many key questions in materials science, thereby becoming an international authority in phase transitions in both functional materials and nonlinear excitations in low - dimensional electronic materials.

This workshop explored mathematical tools and problems in describing the life cycle, stage conversion, and clonal expansion of T. gondii by bringing together expertise in parasitic diseases, epidemiology, population genetics, disease modeling, network dynamics, evolutionary dynamics, and nonlinear analysis.

The framework is based on solving nonlinear coupled ordinary and partial differential equations that model the kinetics of the following phenomena: (1) mass transport in the electrolyte and electrode using the Nernst - Planck equation; (2) electrical potential distribution using the Poisson equation; (3) interfacial reactions that determine the boundary conditions or source terms (using the Butler - Volmer equation or constant - flux conditions); and (4) evolution of the electrode / electrolyte interface using the Allen - Cahn equation within the phase - field modeling (PFM) approach.

The core facility is a two - photon in vivo imaging platform developed at the Nonlinear bioimaging laboratory, a technique that allows for non-invasive structural and functional measurements in small animal models at different scales: from macroscopic imaging of the brain morphology to highly resolved microscopy of neuron populations, single neurons, and even subcellular structures.

Earlier models attributed these kinematic properties to nonlinear neural circuitry in the brainstem but this creates problems for oblique saccades.

Linear and nonlinear computational models must be validated in order to establish confidence in the prediction and understanding of tokamak disruption physics with and without mitigation.

Simple models are very different, and are more like an effective sensitivity and may well lack some of the nonlinear dynamics / regional processes that occur in the real world and, in a more limited way, in the complex models.

They conclude, based on study of CMIP5 model output, that equilibrium climate sensitivity (ECS) is not a fixed quantity — as temperatures increase, the response is nonlinear, with a smaller effective ECS in the first decades of the experiments, increasing over time.

You see, the human body is a nonlinear system and things like the calories in versus calories out model — a linear system — at best, give us only a guide of how things will go.

The role of positivity and connectivity in the performance of business teams: A nonlinear dynamics model.

Suppose we had seven guys in the room, an economist, a guy from a ratings agency, an actuary, a guy who does capital structure arbitrage, a derivatives trader, A CDO manager, and a guy who does nonlinear dynamic modeling, and we asked them what the spread on a corporate bond should be.

But, on the basis of studies of nonlinear chaotic models with preferred states or «regimes», it has been argued, that the spatial patterns of the response to anthropogenic forcing may in fact project principally onto modes of natural climate variability.

Topics will include predictability, ensemble prediction, nonlinear prediction, nonlinear time series analysis, low - dimensional chaos, error growth in the models, nonlinear modeling, fractals and multifractals, bifurcation, and other aspects of nonlinear science.

For example, Hansen's recent paper on Scientific Reticence is quite explicit that much of important physics of ice sheets is not included in the models, hence his raising of matters to do with nonlinear behaviour (eg disintegration) of ice sheets.

• Lack of formal model verification & validation, which is the norm for engineering and regulatory science • Circularity in arguments validating climate models against observations, owing to tuning & prescribed boundary conditions • Concerns about fundamental lack of predictability in a complex nonlinear system characterized by spatio - temporal chaos with changing boundary conditions • Concerns about the epistemology of models of open, complex systems

O'Gorman, P. A., and T. Schneider, 2007: Recovery of atmospheric flow statistics in a general circulation model without nonlinear eddy - eddy interactions.

Thus, are we getting closer to modeling ice sheet dynamics in a nonlinear fashion?

Nonlinear Single - Degree - of - Freedom Models in Earthquake Engineering.

Finite precision computer realizations of nonlinear models give unrealistic solutions because of deterministic chaos, a direct consequence of round - off error growth in iterative numerical computations.»

Issues remain over the proper treatment of thermobaricity (nonlinear relationship of temperature, salinity and pressure to density), which means that in some isopycnic coordinate models the relative densities of, for example, Mediterranean and Antarctic Bottom Water masses are distorted.

The well known example of Lorentz is true in a discretized deterministic nonlinear atmospheric model.

Given the range of possible outcomes of nonlinear processes in individual models — the usefulness of this is a matter of perspective.

This spread results because the model equations provide a deterministic set of results that each can be different since the climate is a chaotic nonlinear system both in the model, and even more so in the real world.

The model output is evidence of the result of the many processes working together, much as the Pythagorean theorem provides evidence about the hypoteneuses of a large set imperfectly studied right triangles; or long term simulations of the planetary movements based on Newton's laws provide evidence that the orbits are chaotic rather than periodic; or simulations provide evidence that high - dimensional nonlinear dissipative systems are never in equilibrium or steady state even with constant input.

The other problem is a mathematical one, in terms of how you actually evaluate with observations a model with a very large number of degrees of freedom that is nonlinear / chaotic as well.

In a system such as the climate, we can never include enough variables to describe the actual system on all relevant length scales (e.g. the butterfly effect — MICROSCOPIC perturbations grow exponentially in time to drive the system to completely different states over macroscopic time) so the best that we can often do is model it as a complex nonlinear set of ordinary differential equations with stochastic noise terms — a generalized Langevin equation or generalized Master equation, as it were — and average behaviors over what one hopes is a spanning set of butterfly - wing perturbations to assess whether or not the resulting system trajectories fill the available phase space uniformly or perhaps are restricted or constrained in some waIn a system such as the climate, we can never include enough variables to describe the actual system on all relevant length scales (e.g. the butterfly effect — MICROSCOPIC perturbations grow exponentially in time to drive the system to completely different states over macroscopic time) so the best that we can often do is model it as a complex nonlinear set of ordinary differential equations with stochastic noise terms — a generalized Langevin equation or generalized Master equation, as it were — and average behaviors over what one hopes is a spanning set of butterfly - wing perturbations to assess whether or not the resulting system trajectories fill the available phase space uniformly or perhaps are restricted or constrained in some wain time to drive the system to completely different states over macroscopic time) so the best that we can often do is model it as a complex nonlinear set of ordinary differential equations with stochastic noise terms — a generalized Langevin equation or generalized Master equation, as it were — and average behaviors over what one hopes is a spanning set of butterfly - wing perturbations to assess whether or not the resulting system trajectories fill the available phase space uniformly or perhaps are restricted or constrained in some wain some way.

In the long term, forward, process - based models of proxy formation are needed for explicitly representing multivariate, nonlinear, and potentially nonstationary relationships between the proxy and climate systems [Evans et al., 2013].

And to: «ENSO dynamics in current climate models: an investigation using nonlinear dimensionality reduction» http://www.nonlin-processes-geophys.net/15/339/2008/npg-15-339-2008.pdf

In this case in particular, the correct formulae are the full nonlinear Navier - Stokes equations with external forcings, implemented in a full thermal model of the EartIn this case in particular, the correct formulae are the full nonlinear Navier - Stokes equations with external forcings, implemented in a full thermal model of the Eartin particular, the correct formulae are the full nonlinear Navier - Stokes equations with external forcings, implemented in a full thermal model of the Eartin a full thermal model of the Earth.

The essential problem in projecting solutions forward is that there is no single deterministic solution to the nonlinear equations and no expectation that future states can be modeled at all.

Any change in a model can produce divergent solutions that are not predictable beforehand — it is the nature of the nonlinear Navier - Stokes equations — this extends to the range of uncertainty in climate data and to the number and breadth of couplings.

For one thing, they're linear models, in which the impacts of various factors (man - made greenhouse gases, ENSO, natural climate forcings) are additive, but while that is often a good approximation, the real world is nonlinear.

The biggest scientific contribution that Hansen and his colleagues make is an attempt to nail down a Moore's law (which models nonlinear rates of growth in computer chips) to ice sheets: Assuming non-linear processes have already begun, how fast will Greenland and Antarctica melt?

What the red team needs is an explanation in single syllables of what is and is not theoretically answerable using these high level nonlinear models.

In this study, evidence for a nonlinear association between ENSO and precipitation extremes is reassessed by fitting stationary and linear / nonlinear GEV regression models, with the Niño3.4 index as a covariate, to 1 -, 5 -, and 10 - day extended winter precipitation maxima.

IMO, the standard 1D energy balance model of the Earth's climate system will provide little in the way of further insights; rather we need to bring additional physics and theory (e.g. entropy and the 2nd law) into the simple models, and explore the complexity of coupled nonlinear climate system characterized by spatiotemporal chaos.

There are mathematical fatal flaws in all the models that can not be overcome even if supercomputers improve by an order of magnitude, and if Rob Ellisons nonlinear dynamic chaos concerns can be overcome by enough ensemble runs to discern their main climate strange attractors.

Optimum Niño3.4 breakpoints are positive (> +0.4 °C) in the majority of the nonlinear models, confirming that ENSO / precipitation relationships differs between La Niña / neutral and El Niño winters.

Any change in a model can produce divergent solutions that are not predictable beforehand — it is the nature of the nonlinear Navier - Stokes equations.

Both models and climate are coupled, nonlinear chaotic systems — acknowledged in the TAR at least.

At the species level, a significant increase in tree mortality was found in seven of the nine most common tree species [Fig. 2B; P < 0.0001, generalized nonlinear mixed model (GNMM)-RSB-.

And, through a transformation of state variables, you can reduce the expansion to a smaller set of ODEs, with a nonlinear relationship for the observable, with well separated resonant frequencies in the model.

Start a variety of model runs with different initial conditions, and they would show, like most calculations with complex nonlinear feedbacks, random variations in the weather patterns computed for one or another region and season.

In those studies, sea ice exhibits nonlinear behavior such that when it is reduced below a certain threshold (the «Small Ice Cap Instability» threshold), the model sea ice abruptly reverts to year - round ice - free conditions.

Sun (March 2016): Weak ENSO asymmetry due to weak nonlinear air — sea interaction in CMIP5 climate models.

Of course, even if we had a perfect model, that model would have to be discretized to solve, and the error in integrating such a nonlinear system forward in time would be extremely challenging, most likely impossible.