scholarly journals Simulasi Monte Carlo untuk Memprediksi Persediaan Darah

2020 ◽  
Author(s):  
Rahmi Darnis ◽  
Gunadi Widi Nurcahyo ◽  
Yuhandri Yunus
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Blood Supply ◽  
Transport System ◽  
Real Data ◽  
Transportation System ◽  
Production Data ◽  
Accuracy Rate ◽  
Simulation Results

Blood is a special organ as a communication and transportation system whose job is to circulate nutrients and oxygen. As a very vital transport system and its very useful existence for many people, blood must be managed properly. Monte Carlo simulations can predict problems related to blood stock and demand for blood. The data that is processed to predict blood supply is blood production data in 2018 and 2019, Simulation results data for 2018 are compared with real data for 2019 and simulation results for 2019 are compared with real data for 2020. The results of the simulations that have been carried out have an accuracy rate of 96.21% for 2018 and 79.22% for 2019. Based on the results of the tests that have been done, it can provide information that can help in the management of forecasting future blood stocks.

On the computational estimation of high order GARCH model

2021 ◽  
Vol 8 (4) ◽  
pp. 797-806
Author(s):  
A. Settar ◽  
◽  
N. I. Fatmi ◽  
M. Badaoui ◽  
◽  
...  
Keyword(s):  
Monte Carlo ◽  
Kalman Filter ◽  
Monte Carlo Simulations ◽  
Garch Model ◽  
Real Data ◽  
Conditional Variance ◽  
High Order ◽  
Computational Estimation ◽  
Necessary And Sufficient ◽  
The Garch Model

To guarantee the non-negativity of the conditional variance of the GARCH process, it is sufficient to assume the non-negativity of its parameters. This condition was empirically violated besides rendering the GARCH model more restrictive. It was subsequently relaxed for some GARCH orders by necessary and sufficient constraints. In this paper, we generalized an approach for the QML estimation of the GARCH(p,q) parameters for all orders $p\geq 1$ and $q\geq1$ using a constrained Kalman filter. Such an approach allows a relaxed QML estimation of the GARCH without the need to identify and/or apply the relaxed constraints to the parameters. The performance of our method is demonstrated through Monte Carlo simulations and empirical applications to real data.

scholarly journals MULTILEVEL BLOCKING MONTE CARLO SIMULATIONS FOR QUANTUM DOTS

2001 ◽  
Vol 15 (10n11) ◽  
pp. 1416-1425 ◽  
Author(s):  
R. EGGER ◽  
C. H. MAK
Keyword(s):  
Quantum Dots ◽  
Monte Carlo ◽  
Low Temperature ◽  
Monte Carlo Simulations ◽  
Strongly Correlated Electrons ◽  
Correlated Electrons ◽  
Strongly Correlated ◽  
Path Integral Monte Carlo ◽  
Sign Problem ◽  
Simulation Results

This article provides an introduction to the ideas behind the multilevel blocking (MLB) approach to the fermion sign problem in path-integral Monte Carlo simulations, and also gives a detailed discussion of MLB results for quantum dots. MLB can turn the exponential severity of the sign problem into an algebraic one, thereby enabling numerically exact studies of otherwise inaccessible systems. Low-temperature simulation results for up to eight strongly correlated electrons in a parabolic 20 quantum dot are presented.

Analyzing Push Schemes for Social Networking Services in Wireless Networks by Using Monte Carlo Simulations

2013 ◽  
Vol 717 ◽  
pp. 760-765
Author(s):  
Kyung Koo Jun
Keyword(s):  
Monte Carlo ◽  
Wireless Networks ◽  
Monte Carlo Simulations ◽  
Social Networking ◽  
Everyday Life ◽  
Weighting Factor ◽  
Social Networking Services ◽  
Simulation Results ◽  
Push And Pull ◽  
Do So

Social networking services such as Twitter and Facebook have occupied a large portion of our everyday life and it is expected to do so for the time being. SNS systems use both push and pull schemes to deliver contents to users. Regarding the push schemes, there are push N based scheme and timer based scheme. In this paper, we analyze the performance of both schemes by using Monte Carlo simulations and understand their characteristics. We present the simulation results that show the performance under various conditions. Moreover, we find that a weighting factor should be given more emphasis because of its significant impact on the performance. Also, we claim that the former work that analyzed PNS and TPS used wrong assumption that leads to the misconception about PNS.

Analisis dan Implementasi Simulasi Monte Carlo untuk Prediksi Kebutuhan Gula berdasarkan Penjualan Bumbu Tabur XYZ

Jurnal METRIS ◽  
2020 ◽  
Vol 21 (02) ◽  
pp. 103-110
Author(s):  
Chendrasari Wahyu Oktavia ◽  
Christine Natalia ◽  
Ferdian Suprata ◽  
Astria Hindratmo
Keyword(s):  
Monte Carlo ◽  
Control Method ◽  
Real Data ◽  
Raw Material ◽  
Material Control ◽  
Simulation Based ◽  
Material Requirement ◽  
Simulation Results ◽  
The Difference ◽  
A Company

The sales activity is a very important activity for the development and sustainability of a company. The sales are closely related to the requirement of raw material. By knowing the number of sales, a company can do estimate the amount of raw material required for production. However, so far still be found as a company that has its policies to determine a requirement of raw material as impact not use a raw material control method. The research purpose to determine the amount of sugar raw material requirement based on results number of sales seasoning XYZ with Monte Carlo simulation. Based on the analysis of data processing results. It was found that the number of sales from the simulation results in 2019 was quite high compared to the sales results during 2018 where the difference in sales simulation in 2019 and real data in 2018 was 62,334 kg. In terms of sugar supply, the total requirement for sugar in 2019 is also quite high, namely 186,756 kg, or the difference in requirement between simulation results and real data is 21,818 kg. This shows that the amount of requirement is directly proportional to sales.

Use of Monte Carlo Modeling to Aid Interpretation and Quantification of the Low Energy-Loss Electron Yield at Low Primary Energies

2008 ◽  
Vol 14 (5) ◽  
pp. 439-450 ◽  
Author(s):  
Christopher Bonet ◽  
Andrew Pratt ◽  
Mohamed M. El-Gomati ◽  
Jim A.D. Matthew ◽  
Steven P. Tear
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
High Vacuum ◽  
Stopping Power ◽  
Low Loss ◽  
Yield Curves ◽  
Beam Sample ◽  
Detector Geometry ◽  
Simulation Results ◽  
Lle Data

AbstractExperimental low-loss electron (LLE) yields were measured as a function of loss energy for a range of elemental standards using a high-vacuum scanning electron microscope operating at 5 keV primary beam energy with losses from 0 to 1 keV. The resulting LLE yield curves were compared with Monte Carlo simulations of the LLE yield in the particular beam/sample/detector geometry employed in the experiment to investigate the possibility of modeling the LLE yield for a series of elements. Monte Carlo simulations were performed using both the Joy and Luo [Joy, D.C. & Luo, S., Scanning11(4), 176–180 (1989)] expression for the electron stopping power and recent tabulated values of Tanuma et al. [Tanuma, S. et al., Surf Interf Anal37(11), 978–988 (2005)] to assess the influence of the more recent stopping power data on the simulation results. Further simulations have been conducted to explore the influence of sample/detector geometry on the LLE signal in the case of layered samples consisting of a thin C overlayer on an elemental substrate. Experimental LLE data were collected from a range of elemental samples coated with a thin C overlayer, and comparisons with Monte Carlo simulations were used to establish the overlayer thickness.

Three Dimensional Monte Carlo Simulations with Real Grain Orientations for the Role of Sub-Boundaries and Precipitates in Abnormal Grain Growth

2013 ◽  
Vol 753 ◽  
pp. 367-372
Author(s):  
Tae Wook Na ◽  
Chang Soo Park ◽  
Hyung Seok Shim ◽  
Byeong Joo Lee ◽  
Chan Hee Han ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Solid State ◽  
Monte Carlo Simulations ◽  
Grain Growth ◽  
Three Dimensional ◽  
Abnormal Grain Growth ◽  
Grain Orientations ◽  
The Matrix ◽  
Simulation Results

Three-dimensional Monte Carlo simulations with real grain orientations are performed to study the role of precipitates and sub-boundaries in the abnormal grain growth. According to the simulation results, sub-boundaries in the abnormally growing grain and precipitates in the matrix grains are necessary for the abnormal grain growth. The simulation results can be best explained by the mechanism of sub-boundary enhanced solid state wetting. The simulated microstructure is very similar to that experimentally observed.

SIMULATION STUDIES OF THE IMPURE ATOMS DIFFUSION ON Cu(001) SURFACE

2004 ◽  
Vol 18 (17n19) ◽  
pp. 2766-2770
Author(s):  
GUOCE ZHUANG
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Critical Point ◽  
Kinetic Monte Carlo ◽  
Diffusion Mechanism ◽  
Indium Atom ◽  
Simulation Studies ◽  
Kinetic Monte Carlo Simulations ◽  
Simulation Results ◽  
Close Packed Layer

Based on the vacancy-assisted diffusion mechanism, the impure atomic moving processes on the close-packed layer of a Cu (001) surface are studied by kinetic Monte Carlo simulations. Our simulation results show that the diffusivity of the Indium atom agrees quite well with the exact lattice solution. In addition, it is found that in the case of muti-impure atoms, there exist a critical point near the value of ∊=0, and the diffusivity of In atom depends on the number of impure atoms only when ∊ is positive.

scholarly journals Small area estimation in the case of nonesponse

2009 ◽  
Vol 50 ◽  
Author(s):  
Vilma Nekrašaitė-Liegė
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Small Area ◽  
Finite Population ◽  
Real Data ◽  
Area Estimation ◽  
Empirical Results ◽  
Different Types ◽  
Business Survey ◽  
Repeated Samples

In this paper the effect of model and nonresponseadjustment on different types of estimators for the totals of small area domains is examined. The empirical results are based on Monte Carlo simulations with repeated samples drawn from a finite population constructed from the real data from the Lithuanian Business Survey.

scholarly journals The validity of the kinetic collection equation revisited – Part 2: Simulations for the hydrodynamic kernel

2010 ◽  
Vol 10 (3) ◽  
pp. 6219-6240
Author(s):  
L. Alfonso ◽  
G. B. Raga ◽  
D. Baumgardner
Keyword(s):  
Differential Equation ◽  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Numerical Solution ◽  
Mass Distribution ◽  
Total Mass ◽  
Analytic Solution ◽  
Numerical Solutions ◽  
Integro Differential Equation ◽  
Simulation Results

Abstract. The kinetic collection equation (KCE) has been widely used to describe the evolution of the average droplet spectrum due to the collection process that leads to the development of precipitation in warm clouds. This deterministic, integro-differential equation only has analytic solution for very simple kernels. For more realistic kernels, the KCE needs to be integrated numerically. In this study, the validity time of the KCE for the hydrodynamic kernel is estimated by a direct comparison of Monte Carlo simulations with numerical solutions of the KCE. The simulation results show that when the largest droplet becomes separated from the smooth spectrum, the total mass calculated from the numerical solution of the KCE is not conserved and, thus, the KCE is no longer valid. This result confirms the fact that for realistic kernels appropriate for precipitation development within warm clouds, the KCE can only be applied to the continuous portion of the mass distribution.

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