Monte-Carlo-based approach
A Monte Carlo Based Approach for Groundwater Chemistry Inverse Modeling
... modified Monte-Carlo-based geochemical modeling strategy is proposed to con- strain the parameter space ...is based on the Metropolis-Hastings algorithm [11], a Markov- Chain-based ...
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An Improved Clustering based Monte Carlo Localization approach for Cooperative Multi-robot Localization
... probabilistic approach for cooperative multi-robot localization in indoor ...Our approach is based on Monte Carlo localization that has been applied with great practical success to ...
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Estimation of Admixture Proportions: A Likelihood-Based Approach Using Markov Chain Monte Carlo
... In admixture studies, the choice of the parental popu- lations is often crucial. In most cases the exact parental populations cannot be identified with certainty (in fact it may not even be clear whether a “hybrid” ...
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Monte Carlo sampling approach to stochastic programming
... How one can evaluate quality of a given solution ˆ x ∈ X ? There are two basic approaches to validation of a given solution: (i) Evaluate the gap f (ˆ x ) − v 0 . (ii) Verify the KKT optimality conditions at ˆ x . The ...
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State-of-the-art in Comprehensive Cascade Control Approach through Monte-Carlo Based Representation
... organized based upon the realization of double closed loop to deal with the rotational angles and its rates, while a number of propellant engine modes including on and off are taken into ...quaternion based ...
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Monte Carlo-based quantitative pinhole SPECT reconstruction using a ray-tracing back-projector
... As opposed to the TARCs, the ARCs exhibit volume-dependent underestimation, as dem- onstrated in Fig. 4. Generally, a smaller sphere means lower recovery. The exception to this rule, the 2-mL sphere in water, can ...
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A Multivariate Analysis for Risk Capital Estimation in Insurance Industry: Vine Copulas
... supple approach due to its representation as a mixture of independent Beta densities, but not the solution to all modeling ...flexible approach of solvency capital requirement based on Monte ...
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An Approach to Quantifying Uncertainty in Estimates of Intensity Duration Frequency (IDF) Curves
... uncertainty. Based on these classifications, the sources of uncertainties could be established through modeling extreme hydrologic events, as shown in Figure 2-1 (Xu et ...primarily based on the condition ...
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A simple approach to study the performance of electron Monte Carlo algorithm in cancer treatment using medical Linear Accelerator
... electron Monte is based upon Monte Carlo In this study, a simple performance of this algorithm for The eMC calculated values of different dosimetric quantities such as treatment re compared ...
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A Data Association Algorithm for Multiple Object Tracking in Video Sequences
... The Monte Carlo approach relies on a sample- based construction to represent the state pdf. Mul- tiple particles (samples) of the state are generated, each one associated with a weight which ...
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Simulating the drug discovery pipeline: a Monte Carlo approach
... Virtual projects are created and progress through the drug discovery pipeline by successfully passing a series of go/no-go decision points based on a random number assignment and comparison against the user ...
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Experience based Reinforcement Learning to Acquire Effective Behavior in a Multiagent Domain
... learning approach (which is similar to a Monte-Carlo based reinforcement learning method) that can be used to learn robust and eective actions within uncertain, dynamic, multi-agent ...
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RAVEN: A GUI and an Artificial Intelligence Engine in a Dynamic PRA Framework
... a Monte Carlo sampling capability, and it is currently used to sample the RELAP-7 input ...surface approach based on the present Monte Carlo to generate the training set and the ...
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PROCEEDINGS OF SPIE. Zhang, Y., Zhang, C., Nestler, R., Rosenberger, M., Notni, G.
... system based on Convolutional Neural Networks (CNN) and Monte Carlo ...the approach, CNN is used for preprocessing and offline ...filter approach. Experiments will show that our ...
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Derivation and evaluation of landslide triggering thresholds by a Monte Carlo approach
... initial wetness on triggering rainfall is neglected. Regarding this issue, several authors have added to D and I antecedent rainfall as a control parameter, though the empirical analy- ses have not yet provided ...
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Examples of Monte Carlo techniques applied for nuclear data uncertainty propagation
... is based on a linear-approach and large uncertainties may exceed the range of linearity of the model, and 3) it shows severe limitations as consequence of the non-linearity of multi-physics (neutronics, ...
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A Quantum Monte Carlo approach to dark matter-nuclei interaction
... • Motion of galaxies — Historically, the presence of non-luminous mat- ter in the universe was proposed to explain the discrepancy between the motion of galaxies and the visible mass, deduced from the measure of ...
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Collectivity in Heavy Nuclei in the Shell Model Monte Carlo Approach
... is based on the Hubbard-Stratonovich (HS) transformation [9], in which the Gibbs oper- ator e − βH of a nucleus described by a Hamiltonian H at inverse temperature β = 1/T is represented as a superposition of ...
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Criticality Analysis and Quality Appraisal of Innoson Injection Mould System
... is based on systems and process that support global ...employed Monte Carlo Normal distribution model which interacts with a developed Obudulu model to assess reliability and maintenance of Injection ...
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Monte Carlo Simulation
... We know from Discrete Time Finance that one can compute a fair price for an option by taking an expectation.. E Q e − rT X.[r] ...
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