scholarly journals Application of statistical simulation for avalanche-risk evaluation

2001 ◽  
Vol 32 ◽  
pp. 182-186 ◽  
Author(s):  
P. A. Chernouss ◽  
Yu. Fedorenko
Keyword(s):  
Risk Evaluation ◽  
Input Data ◽  
Risk Estimation ◽  
Probability Distributions ◽  
Statistical Simulation ◽  
Integrated System ◽  
Computer Assisted ◽  
Deterministic Models ◽  
Avalanche Dynamics ◽  
Avalanche Risk

AbstractAvalanche risk is considered as the probability of an avalanche event that could cause certain losses. A unified approach for avalanche-risk evaluation by statistical simulation is suggested. A chain of models, describing snow deposition, transformation, stability, avalanche dynamics and interaction with an obstacle, is used within such an approach. Each of the models evaluates a given situation in a deterministic manner, yielding a unique result value. Output data of each model can be the input for the next model in the chain. Uncertainty of input data is described in a probabilistic manner. Using the chain of the deterministic models and simulating the input data according to appropriate probability distributions with the Monte Carlo method, risk evaluations are obtained as the ratio of a number of certain types of outcome to the total number of tests. All kinds of information on weather, snow and avalanches can be used within this scheme. The simulation process can be started at any stage of the modelling. In this study it was started from the snow-cover stability simulation. Application of the statistical simulation in such a way gives an opportunity to reflect uncertainty of the initial data in the results obtained. The suggested scheme was used for producing a computer-assisted workplace for avalanche forecasting, “LAVINA”, which has been exploited at the Centre of Avalanche Safety of “Apatit”, Kirovsk, Russia, since the early 1990s. It is an integrated system that permits spatial and temporal estimations of snow stability and avalanche dynamics to be made. Assessments of the validity of the risk estimation made with LAVINA are presented.

scholarly journals Use of Bayesian population viability analysis to assess multiple management decisions in the recovery programme for the Endangered takahe Porphyrio hochstetteri

Oryx ◽  
2013 ◽  
Vol 47 (1) ◽  
pp. 144-152 ◽  
Author(s):  
Danilo Hegg ◽  
Darryl I. MacKenzie ◽  
Ian G. Jamieson
Keyword(s):  
Probability Distributions ◽  
Management Strategies ◽  
Population Viability Analysis ◽  
Experimental Manipulation ◽  
Population Modelling ◽  
Deterministic Models ◽  
Logistic Regression Models ◽  
Viability Analysis ◽  
Management Actions ◽  
Captive Rearing

AbstractPopulation modelling is an invaluable tool for identifying effective management strategies for threatened species whose populations are too small for experimental manipulation. Recently developed Bayesian approaches allow us to combine deterministic models with probability distributions to create stochastic models that account for uncertainty. We illustrate this approach in the case of the takahe Porphyrio hochstetteri, an Endangered flightless rail, which is supported by one of New Zealand's costliest recovery programmes. Using mark–recapture and logistic regression models implemented in a Bayesian framework we calculated demographic parameters for a fully stochastic population model based on 25 years of data collected from the last wild population of takahe in the Murchison Mountains, Fiordland. Our model results show that stoat trapping, captive rearing and cross-fostering of eggs/chicks in wild pairs all have a positive effect on takahe demography. If it were not for these management actions the Fiordland population would probably be declining (λ = 0.985; confidence interval, CI = 0.39–1.08), with a non-negligible risk of quasi-extinction (P = 16%) within 20 years. The captive rearing of eggs and chicks has been the main factor responsible for the positive growth observed during the last decade but in the future expanding stoat trapping to cover the entire Murchison Mountains would be the single most beneficial management action for the takahe population (λ = 1.038; CI = 0.86–1.10), followed by captive rearing (λ = 1.027; CI = 0.85–1.09).

scholarly journals Probabilistic Motion Estimation Based on Temporal Coherence

2000 ◽  
Vol 12 (8) ◽  
pp. 1839-1867 ◽  
Author(s):  
Pierre-Yves Burgi ◽  
Alan L. Yuille ◽  
Norberto M. Grzywacz
Keyword(s):  
Computer Simulations ◽  
Kalman Filtering ◽  
Input Data ◽  
Visual Motion ◽  
Probability Distributions ◽  
Temporal Integration ◽  
Spatial Coherence ◽  
Image Sequence ◽  
Temporal Grouping ◽  
Parallel Network

We develop a theory for the temporal integration of visual motion motivated by psychophysical experiments. The theory proposes that input data are temporally grouped and used to predict and estimate the motion flows in the image sequence. This temporal grouping can be considered a generalization of the data association techniques that engineers use to study motion sequences. Our temporal grouping theory is expressed in terms of the Bayesian generalization of standard Kalman filtering. To implement the theory, we derive a parallel network that shares some properties of cortical networks. Computer simulations of this network demonstrate that our theory qualitatively accounts for psychophysical experiments on motion occlusion and motion outliers. In deriving our theory, we assumed spatial factorizability of the probability distributions and made the approximation of updating the marginal distributions of velocity at each point. This allowed us to perform local computations and simplified our implementation. We argue that these approximations are suitable for the stimuli we are considering (for which spatial coherence effects are negligible).

scholarly journals Eliciting opinions of experts using uncertainty

2015 ◽  
Vol 56 ◽  
Author(s):  
Valentinas Podvezko ◽  
Askoldas Podviezko
Keyword(s):  
Decision Making ◽  
Probability Distribution ◽  
Decision Aid ◽  
Probability Distributions ◽  
Multiple Criteria Decision Making ◽  
Simulation Method ◽  
Statistical Simulation ◽  
Expert Evaluation ◽  
Absolute Level ◽  
Level Of Importance

Multiple criteria decision-making (MCDM) methods designed for evaluation of attractiveness of available alternatives, whenever used in decision-aid systems, imply active participation of experts. They participate in all stages of evaluation: casting a set of criteria, which should describe an evaluated process or an alternative; estimating level of importance of each criterion; estimating values of some criteria and sub-criteria. Social and economic processes are prone to laws of statistics,which are described and could be forecasted using the theory of probability. Weights of criteria, which reveal levels of their importance, could rarely be estimated with the absolute level of precision. Uncertainty of evaluation is characterised by a probability distribution. Aiming to elicit evaluation from experts we have to find either a distribution or a density function. Statistical simulation method can be used for estimation of evaluation of weights and/or values of criteria by experts. Alternatively, character of related uncertainty can be estimated by an expert himself during the survey process. The aim of this paper is to describe algorithms of expert evaluation with estimation of opinion uncertainty, which were applied in practice. In particular, a new algorithm was proposed, where an expert evaluates criteria by probability distributions.

scholarly journals Reconstruction of Complex Zygomatic Bone Defects Using Mirroring Coupled with EBM Fabrication of Titanium Implant

Metals ◽  
2019 ◽  
Vol 9 (12) ◽  
pp. 1250 ◽  
Author(s):  
Khaja Moiduddin ◽  
Syed Hammad Mian ◽  
Usama Umer ◽  
Naveed Ahmed ◽  
Hisham Alkhalefah ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Electron Beam ◽  
Titanium Implant ◽  
Integrated System ◽  
Implant Design ◽  
Computer Assisted ◽  
Biomechanical Behavior ◽  
Aesthetic Appearance ◽  
System Methodology ◽  
Zygomatic Implant

Reconstruction of zygomatic complex defects is a surgical challenge, owing to the accurate restoration of structural symmetry as well as facial projection. Generally, there are many available techniques for zygomatic reconstruction, but they hardly achieve aesthetic and functional properties. To our knowledge, there is no such study on zygomatic titanium bone reconstruction, which involves the complete steps from patient computed tomography scan to the fabrication of titanium zygomatic implant and evaluation of implant accuracy. The objective of this study is to propose an integrated system methodology for the reconstruction of complex zygomatic bony defects using titanium comprising several steps, right from the patient scan to implant fabrication while maintaining proper aesthetic and facial symmetry. The integrated system methodology involves computer-assisted implant design based on the patient computed tomography data, the implant fitting accuracy using three-dimensional comparison techniques, finite element analysis to investigate the biomechanical behavior under loading conditions, and finally titanium fabrication of the zygomatic implant using state-of-the-art electron beam melting technology. The resulting titanium implant has a superior aesthetic appearance and preferable biocompatibility. The customized mirrored implant accurately fit on the defective area and restored the tumor region with inconsequential inconsistency. Moreover, the outcome from the two-dimensional analysis provided a good accuracy within 2 mm as established through physical prototyping. Thus, the designed implant produced faultless fitting, favorable symmetry, and satisfying aesthetics. The simulation results also demonstrated the load resistant ability of the implant with max stress within 1.76 MPa. Certainly, the mirrored and electron beam melted titanium implant can be considered as the practical alternative for a bone substitute of complex zygomatic reconstruction.

scholarly journals Probabilistic Forecasting of Nitrogen Dioxide Concentrations at an Urban Road Intersection

2018 ◽  
Vol 10 (11) ◽  
pp. 4213 ◽  
Author(s):  
Joanna Kamińska
Keyword(s):  
Wind Speed ◽  
Nitrogen Dioxide ◽  
City Planning ◽  
Probability Distributions ◽  
Large City ◽  
Probabilistic Forecasting ◽  
Deterministic Models ◽  
Principal Mechanism ◽  
Complex Processes ◽  
Input Variables

The concentration of nitrogen dioxide in the air along a major route in a large city is affected by very many factors, which are also interdependent. As an alternative to complicated deterministic models based on these complex processes, in this study a probabilistic model for predicting NO2 concentrations is proposed, using a simple accounting cluster-based method for determining probability distributions for tabulated values of ambient factors. Using the example of hourly values of NO2 concentration and data on wind speed and traffic flow for the main intersection in Wrocław (Poland), a model is constructed to predict the frequency of occurrence of concentrations in the form of a probability distribution, for given values of the input variables. The model was successfully verified on data for the first six months of 2018. A mean continuous rank probability score (CRPS) of 9.15 μg/m3 was obtained. In spite of the greater impact of traffic volume on urban NO2 concentrations, as measured by Pearson’s correlation coefficient, for instance, the model indicates that wind speed is also a very important factor—wind being the principal mechanism causing the evacuation of pollutants. This underlines the importance of sustainable city planning with regard to ensuring suitable conditions for the passage of air.

Nonparametric frequency polygon estimation for modeling input data

2019 ◽  
Author(s):  
Stephen Hague ◽  
Simaan AbouRizk
Keyword(s):  
Density Estimation ◽  
Kernel Density Estimation ◽  
Posterior Distribution ◽  
Input Data ◽  
Probability Distributions ◽  
Kernel Density ◽  
Simulation Environment ◽  
Frequency Polygon ◽  
Density Estimators

To construct valid probability distributions solely from input data, this paper compares three nonparametric density estimators: (1) histograms, (2) Kernel Density Estimation, and (3) Frequency Polygon Estimation. A pseudocode is implemented, a practical example is illustrated, and the Simphony.NET simulation environment is used to fit the nonparametric frequency polygon to a set of data to recreate it as a posterior distribution via the Metropolis-Hastings algorithm.

scholarly journals Modelling of snow avalanche dynamics: influence of model parameters

2008 ◽  
Vol 49 ◽  
pp. 38-42 ◽  
Author(s):  
A.N. Bozhinskiy
Keyword(s):  
Dry Friction ◽  
Single Point ◽  
Statistical Simulation ◽  
Distribution Functions ◽  
Snow Avalanche ◽  
Model Parameters ◽  
Cross Point ◽  
Turbulent Friction ◽  
Family Of Curves ◽  
Avalanche Dynamics

AbstractThe three-parameter hydraulic model of snow avalanche dynamics including the coefficients of dry and turbulent friction and the coefficient of new-snow-mass entrainment was investigated. The ‘Domestic’ avalanche site in Elbrus region, Caucasus, Russia, was chosen as the model avalanche range. According to the model, the fixed avalanche run-out can be achieved with various combinations of model parameters. At the fixed value of the coefficient of entrainment me , we have a curve on a plane of the coefficients of dry and turbulent friction. It was found that the family of curves ( me is a parameter) are crossed at the single point. The value of the coefficient of turbulent friction at the cross-point remained practically constant for the maximum and average avalanche run-outs. The conclusions obtained are confirmed by the results of modelling for six arbitrarily chosen avalanche sites: three in the Khibiny mountains, Kola Peninsula, Russia, two in the Elbrus region and one idealized site with an exponential longitudinal profile. The dependences of run-out on the coefficient of dry friction are constructed for all the investigated avalanche sites. The results are important for the statistical simulation of avalanche dynamics since they suggest the possibility of using only one random model parameter, namely, the coefficient of dry friction, in the model. The histograms and distribution functions of the coefficient of dry friction are constructed and presented for avalanche sites Nos 22 and 43 (Khibiny mountains) and ‘Domestic’, with the available series of field data.

Sign in / Sign up

Export Citation Format

Share Document