Monte-Carlo-Based Parametric Motion Estimation Using a Hybrid Model Approach

This paper proposed a hybrid intelligent approach based on empirical mode decomposition (EMD), autoregressive integrated moving average (ARIMA) and Monte Carlo simulation (MCS) methods for multi-step ahead medical tourism (MT) forecasting using explanatory input variables based on two decade real-time recorded database. In the proposed hybrid model, these variables are 1st extracted then medical tourism is forecasted to perform the long term as well as the short term goal and planning in the nation. The multi-step ahead medical tourism is forecasted recursively, by utilizing the 1st forecasted value as the input variable to generate the next forecasting value and this procedure is continued till third step ahead forecasted value. The proposed approach firstly tested and validated by using international tourism arrival (ITA) dataset then proposed approach is implemented for forecasting of medical tourism arrival in nation. In order to validate the performance and accuracy of the proposed hybrid model, a comparative analysis is performed by using Monte Carlo method and the results are compared. Obtained results shows that the proposed hybrid forecasting approach for medical tourism has outperformance characteristics.

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Hydrologic responses of the Zwalm catchment using the REW model: incorporating uncertainty of soil properties

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-3-69-2006 ◽

2006 ◽

Vol 3 (1) ◽

pp. 69-114 ◽

Cited By ~ 1

Author(s):

A. El Ouazzani Taibi ◽

G. P. Zhang ◽

A. Elfeki

Keyword(s):

Monte Carlo ◽

Monte Carlo Method ◽

Hydraulic Conductivity ◽

Model Parameters ◽

Watershed Model ◽

The Monte Carlo Method ◽

Physically Based ◽

Hydrologic Responses ◽

High Influence ◽

Model Approach

Abstract. The research presented in this paper focuses on an application of a newly developed physically-based watershed model approach, which is called Representative Elementary Watershed (REW) approach. The study stressed the effects of uncertainty of input parameters on the watershed responses (i.e. simulated discharges). The approach was applied to the Zwalm catchment, which is an agriculture dominated watershed with a drainage area of 114.3 km2 located in East-Flanders, Belgium. Uncertainty analysis of the model parameters is limited to the saturated hydraulic conductivity because of its high influence on the watershed hydrologic behavior. The assessment of outputs uncertainty is performed using the Monte Carlo method. The ensemble statistical watershed responses and their uncertainties are calculated and compared with the measurements. The results show that the measured discharges are falling within the 95% confidence interval of the modeled discharge.

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Investigating Exchange Rate Dynamics in Mozambique: A Hybrid Model Approach

SSRN Electronic Journal ◽

10.2139/ssrn.3732947 ◽

2020 ◽

Author(s):

Aurélio Bucuane

Keyword(s):

Exchange Rate ◽

Hybrid Model ◽

Exchange Rate Dynamics ◽

Model Approach

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Secondary Fluorescence of 3D Heterogeneous Materials Using a Hybrid Model

Microscopy and Microanalysis ◽

10.1017/s1431927620001531 ◽

2020 ◽

Vol 26 (3) ◽

pp. 484-496

Author(s):

Yu Yuan ◽

Hendrix Demers ◽

Xianglong Wang ◽

Raynald Gauvin

Keyword(s):

Monte Carlo Simulation ◽

Monte Carlo ◽

Analytical Model ◽

Hybrid Model ◽

Three Dimensional ◽

Heterogeneous Materials ◽

X Ray ◽

The Monte Carlo Method ◽

Secondary Fluorescence ◽

Good Agreement

AbstractIn electron probe microanalysis or scanning electron microscopy, the Monte Carlo method is widely used for modeling electron transport within specimens and calculating X-ray spectra. For an accurate simulation, the calculation of secondary fluorescence (SF) is necessary, especially for samples with complex geometries. In this study, we developed a program, using a hybrid model that combines the Monte Carlo simulation with an analytical model, to perform SF correction for three-dimensional (3D) heterogeneous materials. The Monte Carlo simulation is performed using MC X-ray, a Monte Carlo program, to obtain the 3D primary X-ray distribution, which becomes the input of the analytical model. The voxel-based calculation of MC X-ray enables the model to be applicable to arbitrary samples. We demonstrate the derivation of the analytical model in detail and present the 3D X-ray distributions for both primary and secondary fluorescence to illustrate the capability of our program. Examples for non-diffusion couples and spherical inclusions inside matrices are shown. The results of our program are compared with experimental data from references and with results from other Monte Carlo codes. They are found to be in good agreement.

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