scholarly journals Consecutive Scoring Probability Distribution in Volleyball:Applying the Monte-Carlo Simulation

2017 ◽  
Vol 19 (1) ◽  
pp. 39-47
Author(s):  
윤효준 ◽  
JaeHyeon
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Probability Distribution

scholarly journals Simulasi Monte Carlo dalam Memprediksi Penerimaan Peserta Pelatihan Dasar CPNS

2021 ◽  
pp. 134-138
Author(s):  
Faisal Roza ◽  
Sarjon Defit ◽  
Gunadi Widi Nurcahyo
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Probability Distribution ◽  
Civil Servant ◽  
Random Numbers ◽  
Basic Training ◽  
Internal Affairs

The implementation of basic training recruit (latsar) of civil servant (CPNS) at Pusat Pengembangan Sumber Daya Manusia (PPSDM) Ministry of Internal Affairs regional Bukittinggi. The leader takes decision in doing the implementation of latsar CPNS recruit in PPSDM scope regional Bukittinggi. Latsar CPNS is one of requirements to be civil servant. Therefore, it is necessary to collect data by doing observation, interview questionings with related party in the implementation of latsar CPNS recruit from 2018 to 2020. It can be predicted for the next recruit. After doing library references by reading some books and journals, the basic training recruit of CPNS sources from PPSDM regional Bukittinggi, and Monte Carlo simulation. By using Monte Carlo simulation in predicting data, it can get closer value of actual value. Based on distribution of sampling data, the method is by choosing random numbers from probability distribution to do simulation. The Monte Carlo result’s examination has got 173 participants for year 2019, 158 participants for year 2020, and 157 participants for year 2021 clearly. Although the rate of the accurate just reaches 81%, but it has been able to be recommended to help PPSDM regional Bukittinggi, Ministry of Internal Affairs in taking decision and planning for basic training recruit of CPNS for the next.

Operational Risk Evaluation of an Ice Feature Impact

1990 ◽  
Vol 112 (1) ◽  
pp. 96-101
Author(s):  
A. B. Dunwoody
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Probability Distribution ◽  
Stochastic Model ◽  
Risk Evaluation ◽  
Joint Probability ◽  
Joint Probability Distribution ◽  
Offshore Structure ◽  
Simple Stochastic Model ◽  
General Method

The risk of impact by a particular ice feature in the vicinity of an offshore structure or stationary vessel is of concern during operations. A general method is presented for calculating the risk of an impact in terms of the joint probability distribution of the forecast positions and velocities of the ice feature. A simple stochastic model of the motion of an ice feature is introduced for which the joint probability distribution of ice feature position and velocity can be determined as a function of time. The risk of an impact is presented for this model of the motion of an ice feature. Predictions of the distributions of the time until impact and the drift speed upon impact are also presented and discussed. Predictions are compared against results of a Monte Carlo simulation.

Fractional Brownian modeled linear polymer chains with one dimensional Metropolis Monte Carlo simulation

2015 ◽  
Vol 36 ◽  
pp. 1560017
Author(s):  
J. P. B. Sambo ◽  
B. V. Gemao ◽  
J. B. Bornales
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Probability Distribution ◽  
Numerical Data ◽  
Polymer Chains ◽  
Linear Polymer ◽  
Hurst Parameter ◽  
Metropolis Monte Carlo ◽  
End Distance ◽  
Good Agreement

The scaling expression for fractional Brownian modeled linear polymer chains was obtained both theoretically and numerically. Through the probability distribution of fractional Brownian paths, the scaling was found out to be 〈R2〉 ~ N2H, where R is the end-to-end distance of the polymer chain, N is the number of monomer units and H is the Hurst parameter. Numerical data was generated through the use of Monte Carlo simulation implementing the Metropolis algorithm. Results show good agreement between numerical and theoretical scaling constants after some parameter optimization. The probability distribution confirmed the Gaussian nature of fractional Brownian motion and the behavior is not affected by varying values of the Hurst parameter and of the number of monomer units.

scholarly journals Corrigendum to ``Descriptive Measures of Poisson-Lomax Distribution''

2020 ◽  
Vol 43 (2) ◽  
pp. 345-353
Author(s):  
Khushnoor Khan
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Probability Distribution ◽  
Programming Language ◽  
Numerical Results ◽  
Due Diligence ◽  
Mean Values ◽  
Lomax Distribution ◽  
Mathematical Properties ◽  
The Mean

This corrigendum focuses on the correction of numerical results derived from Poisson-Lomax Distribution (PLD) originally proposed by Al-Zahrani & Sagor (2014). Though the mathematical properties and derivations by Al-Zahrani & Sagor (2014) were immaculate but during the execution ofthe R codes using Monte Carlo simulation some anomalies occurred in the calculation of the mean values. The same  anomalies are addressed in thepresent corrigendum. The outcome of the corrigendum will provide basic guidelines for the academia and reviewers of various journals to match thenumerical results with the shape of the probability distribution under study. The results will also emphasize the fact that code writing is a cumbersome process and due diligence be exercised in executing the codes using any programming language. Relevant R codes are appended in Appendix 'A'.

Research of Adaptive Synthesis Rule for Conflict Evidences

2012 ◽  
Vol 532-533 ◽  
pp. 1026-1030
Author(s):  
Sheng Wei Li ◽  
Han Li
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Probability Distribution ◽  
Evidence Synthesis ◽  
The Self ◽  
Synthesis Process ◽  
Balance Function ◽  
High Conflict ◽  
Improvement Method ◽  
Self Adaptation

In order to deal with the lack of treatment with high conflict evidence ability in traditional D-S evidence synthesis rules and some defects of improvement method, an adaptive synthesis rule for conflict evidence is presented. Firstly, based on the balance between conjunction and disjunction, the adaptive synthesis rule for conflict evidence is established; Secondly, the probability distribution of the conflict evidences is gathered by Monte Carlo simulation, and then a reasonable fusion balance function between conjunction and disjunction is established; Thirdly, the conflict coefficient is obtained real-time through conjunction; the self-adaptation of evidence synthesis process is realized simultaneously. Finally, the validity of this method is verified through the comparison with other methods.

scholarly journals Optimizing the Calibration Error of Refraction Angles in Ultrasonic Angle Beam Testing

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1427
Author(s):  
Zhihui Cai ◽  
Zhangmin Jin ◽  
Linyi Zhu ◽  
Yuebing Li ◽  
Yuebao Lei ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Probability Distribution ◽  
Data Fusion ◽  
Ultrasonic Testing ◽  
Calibration Error ◽  
Fusion Method ◽  
Refraction Angle ◽  
Calibration Process ◽  
Mechanical Components

Ultrasonic testing is a useful approach for quantifying the flaws in mechanical components. The height of the flaws in ultrasonic angle beam testing is closely related to the calibration value of the probe refraction angle. In order to reduce the calibration error, some ignored data during the traditional calibration process are reanalyzed and fused to determine the refraction angle. Both arithmetical measurement fusion method and weighted measurement fusion method are applied and compared. Monte Carlo simulation is used to estimate the probability distribution of the refraction angle and obtain the optimal refraction angle weights. Experiments were carried out to verify the results of Monte Carlo simulation. The applicability of data fusion on refraction angles is investigated. It was found in the study that the data fused with the refraction angle is helpful for measuring the height of flaws.

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