scholarly journals The W/S Test for Data Having Neutrosophic Numbers: An Application to USA Village Population

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-8 ◽  
Author(s):  
Mohammed Albassam ◽  
Nasrullah Khan ◽  
Muhammad Aslam
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Statistical Distributions ◽  
Interval Method ◽  
Power Of Test ◽  
Classical Statistics ◽  
Neutrosophic Statistics ◽  
Village Population

The W/S test under neutrosophic statistics is proposed in this paper. The Monte Carlo simulation under the neutrosophic statistical interval method is proposed and applied to study the sensitivity of various neutrosophic statistical distributions. The power of test curves for neutrosophic distributions is presented. The efficiency of the proposed W/S test under neutrosophic statistics is compared with that of the W/S test under classical statistics. The proposed test is explained with the aid of an example.

From Random Tolerances to Random Rotor Vibrations

2002 ◽  
Vol 124 (3) ◽  
pp. 539-542 ◽  
Author(s):  
Oleg Vinogradov
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Explicit Expression ◽  
Statistical Distribution ◽  
Statistical Distributions ◽  
Direct Link ◽  
Unbalanced Mass ◽  
Ring Assembly ◽  
Reaction Forces

In the paper a statistical distribution of reaction forces in a vibrating rotor is traced back to assigned tolerances on components making up this rotor. First, the statistics of the unbalanced mass in an n-ring assembly is considered and an explicit expression for it is derived in terms of tolerances assigned to individual rings. As an illustrative example, the problem of vibrations of a rotor with two assembled disks is considered. The disks are manufactured to different specifications and the statistical distributions of reaction forces are found by Monte Carlo simulation. The latter allows to estimate the probability of vibrations or forces exceeding a specified level for a given accuracy of manufacturing. The methodology presented establishes a direct link between the manufacturing specifications for the components and the quality of performance of the equipment.

scholarly journals Monitoring the Variability in the Process Using Neutrosophic Statistical Interval Method

Symmetry ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 562 ◽  
Author(s):  
Muhammad Aslam ◽  
Nasrullah Khan ◽  
Muhammad Khan
Keyword(s):  
Control Chart ◽  
Control Charts ◽  
Average Run Length ◽  
Interval Methods ◽  
Interval Method ◽  
Classical Statistics ◽  
Neutrosophic Statistics ◽  
Imprecise Observations ◽  
Better Than

Existing variance control charts are designed under the assumptions that no uncertain, fuzzy and imprecise observations or parameters are in the population or the sample. Neutrosophic statistics, which is the extension of classical statistics, has been widely used when there is uncertainty in the data. In this paper, we will originally design S 2 control chart under the neutrosophic interval methods. The complete structure of the neutrosophic S 2 control chart will be given. The necessary measures of neutrosophic S 2 will be given. The neutrosophic coefficient of S 2 control chart will be determined through the neutrosophic algorithm. Some tables are given for practical use. The efficiency of the proposed control chart is shown over the S 2 control chart designed under the classical statistics in neutrosophic average run length (NARL). A real example is also added to illustrate the proposed control chart. From the comparison in the simulation study and case study, it is concluded that the proposed control chart performs better than the existing control chart under uncertainty.

scholarly journals Design of Variable Sampling Plan for Pareto Distribution Using Neutrosophic Statistical Interval Method

Symmetry ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 80 ◽  
Author(s):  
Muhammad Aslam ◽  
Nasrullah Khan ◽  
Ali Hussein AL-Marshadi
Keyword(s):  
Optimization Problem ◽  
Pareto Distribution ◽  
Measurement Data ◽  
Sampling Plan ◽  
Sampling Plans ◽  
Interval Method ◽  
Uncertainty In Measurement ◽  
Variable Sampling ◽  
Classical Statistics ◽  
Neutrosophic Statistics

The sampling plans have been widely used for the inspection of a lot of the product. In practice, the measurement data may be imprecise, uncertain, unclear or fuzzy. When there is uncertainty in the observations, the sampling plans designed using classical statistics cannot be applied for the inspection of a lot of the product. The neutrosophic statistic, which is the generalization of the classical statistics, can be used when data is not precise, uncertain, unclear or fuzzy. In this paper, we will design the variable sampling plan under the Pareto distribution using the neutrosophic statistics. We used the symmetry property of the normal distribution. We assume uncertainty in measurement data and sample size required for the inspection of a lot of the product. We will determine the neutrosophic plan parameters using the neutrosophic optimization problem. Some tables are given for practical use and are discussed with the help of an example.

scholarly journals Optimal Control Methods of Experiment Times in System-of-Systems Combat Computer Simulation

2019 ◽  
Vol 26 ◽  
pp. 03004
Author(s):  
Zhiqiang Zhao ◽  
Feiyue Zhou
Keyword(s):  
Computer Simulation ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Confidence Interval ◽  
Simulation Experiment ◽  
Random Factor ◽  
Interval Method ◽  
Interval Extension ◽  
Self Adaptation ◽  
Optimal Control Methods

In the process of scheme optimization, in order to eliminate the influence of random factor, it needs to conduct computer simulation of Monte Carlo. Therefore, it is proposed to introduce confidence interval into systemof-systems combat simulation, and confirm whether the Monte Carlo simulation finishes according to data sample generated in simulation process. According to characteristic of data sample, extend correspondingly confidence interval method, and under the condition of obtaining the solution meeting accuracy requirements, reduce simulation experiment times as far as possible. The simulation experiment results show that confidence interval extension method is able to possess self-adaptation control to Monte Carlo simulation.

scholarly journals Single-stage and two-stage total failure-based group-sampling plans for the Weibull distribution under neutrosophic statistics

2021 ◽  
Author(s):  
Muhammad Aslam ◽  
G. Srinivasa Rao ◽  
Nasrullah Khan
Keyword(s):  
Weibull Distribution ◽  
Shape Parameter ◽  
Sampling Plan ◽  
Sampling Plans ◽  
Interval Method ◽  
Classical Statistics ◽  
Neutrosophic Statistics ◽  
Total Failure ◽  
Life Tests ◽  
Double Group

AbstractIf the sample or population has vague, inaccurate, unidentified, deficient, indecisive, or fuzzy data, then the available sampling plans could not be suitable to use for decision-making. In this article, an improved group-sampling plan based on time truncated life tests for Weibull distribution under neutrosophic statistics (NS) has been developed. We developed improved single and double group-sampling plans based on the NS. The proposed design neutrosophic plan parameters are obtained by satisfying both producer’s and consumer’s risks simultaneously under neutrosophic optimization solution. Tables are constructed for the selected shape parameter of Weibull distribution and various combinations of neutrosophic group size. The efficiency of the proposed group-sampling plan under the neutrosophic statistical interval method is also compared with the crisp method grouped sampling plan under classical statistics.

scholarly journals A Variable Acceptance Sampling Plan under Neutrosophic Statistical Interval Method

Symmetry ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 114 ◽  
Author(s):  
Muhammad Aslam
Keyword(s):  
Operating Characteristic ◽  
Fuzzy Variable ◽  
Sampling Plan ◽  
Acceptance Sampling ◽  
Interval Method ◽  
Acceptance Sampling Plan ◽  
Variable Sampling ◽  
Classical Statistics ◽  
Neutrosophic Statistics

The acceptance sampling plan plays an important role in maintaining the high quality of a product. The variable control chart, using classical statistics, helps in making acceptance or rejection decisions about the submitted lot of the product. Furthermore, the sampling plan, using classical statistics, assumes the complete or determinate information available about a lot of product. However, in some situations, data may be ambiguous, vague, imprecise, and incomplete or indeterminate. In this case, the use of neutrosophic statistics can be applied to guide the experimenters. In this paper, we originally proposed a new variable sampling plan using the neutrosophic interval statistical method. The neutrosophic operating characteristic (NOC) is derived using the neutrosophic normal distribution. The optimization solution is also presented for the proposed plan under the neutrosophic interval method. The effectiveness of the proposed plan is compared with the plan under classical statistics. The tables are presented for practical use and a real example is given to explain the neutrosophic fuzzy variable sampling plan in the industry.

scholarly journals Monitoring of production of blood components by attribute control chart under indeterminacy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Nasrullah Khan ◽  
Muhammad Aslam ◽  
P. Jeyadurga ◽  
S. Balamurali
Keyword(s):  
Control Chart ◽  
Control Charts ◽  
Blood Components ◽  
Interval Method ◽  
Uncertain Environment ◽  
Classical Statistics ◽  
Neutrosophic Statistics

AbstractThe existing control chart for monitoring the blood components by attribute is designed using classical statistics. The existing attribute control chart can be applied only when the experimenter is sure about the proportion of defective or all the observations in the sample are determined. In this paper, new attribute control charts for monitoring the blood components under the neutrosophic statistics will be presented. The design of the proposed control chart is given under the neutrosophic statistical interval method. The applications of these control charts demonstrate that the proposed control charts are quite effective, adequate, flexible, and informative for monitoring the blood components under uncertain environment.

Tolerance Analysis with EDS/VisVSA

2003 ◽  
Vol 3 (1) ◽  
pp. 95-99 ◽  
Author(s):  
Zhengshu Shen
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
State Of The Art ◽  
Tolerance Analysis ◽  
Statistical Distributions ◽  
Tolerance Range ◽  
Computer Aided ◽  
Cad Models ◽  
Analysis System ◽  
Part Dimension

This paper presents a brief review of a leading commercial computer-aided tolerance (CAT) analysis system, VisVSA, which is available from EDS/Unigraphics. VisVSA facilitates statistical analysis of dimensional variations in parts and assemblies, based on Monte Carlo simulation. Tolerance specific entities and attributes are interactively extracted from CAD models. Feature attributes are varied within the specified tolerance range, and user-defined statistical distributions are used in simulation runs to determine the contributors, the extent of contributions, sensitivities, and statistical distribution of the analyzed part dimension or assembly clearance/interference. VisVSA represents the state-of-the-art in tolerance analysis, but the technology itself needs further advancement.

Electron Scattering in Solids

1990 ◽  
Vol 48 (2) ◽  
pp. 4-5
Author(s):  
Ryuichi Shimizu ◽  
Ze-Jun Ding
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Angular Distribution ◽  
Elastic Scattering ◽  
Electron Scattering ◽  
Cross Sections ◽  
Expansion Method ◽  
Electron Excitation ◽  
Partial Wave Expansion ◽  
Backscattered Electrons

Monte Carlo simulation has been becoming most powerful tool to describe the electron scattering in solids, leading to more comprehensive understanding of the complicated mechanism of generation of various types of signals for microbeam analysis.The present paper proposes a practical model for the Monte Carlo simulation of scattering processes of a penetrating electron and the generation of the slow secondaries in solids. The model is based on the combined use of Gryzinski’s inner-shell electron excitation function and the dielectric function for taking into account the valence electron contribution in inelastic scattering processes, while the cross-sections derived by partial wave expansion method are used for describing elastic scattering processes. An improvement of the use of this elastic scattering cross-section can be seen in the success to describe the anisotropy of angular distribution of elastically backscattered electrons from Au in low energy region, shown in Fig.l. Fig.l(a) shows the elastic cross-sections of 600 eV electron for single Au-atom, clearly indicating that the angular distribution is no more smooth as expected from Rutherford scattering formula, but has the socalled lobes appearing at the large scattering angle.

Determination of Stoichiometry of GaAs Component in (Gaas)Ge Epitaxially Grown Thin Films by Electron Microprobe X-Ray Analysis

1990 ◽  
Vol 48 (2) ◽  
pp. 264-265
Author(s):  
D. R. Liu ◽  
S. S. Shinozaki ◽  
R. J. Baird
Keyword(s):  
Thin Film ◽  
Thin Films ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Compound Semiconductors ◽  
Energy Dispersive Analysis ◽  
X Ray ◽  
Metastable Alloys ◽  
Lower Voltage

The epitaxially grown (GaAs)Ge thin film has been arousing much interest because it is one of metastable alloys of III-V compound semiconductors with germanium and a possible candidate in optoelectronic applications. It is important to be able to accurately determine the composition of the film, particularly whether or not the GaAs component is in stoichiometry, but x-ray energy dispersive analysis (EDS) cannot meet this need. The thickness of the film is usually about 0.5-1.5 μm. If Kα peaks are used for quantification, the accelerating voltage must be more than 10 kV in order for these peaks to be excited. Under this voltage, the generation depth of x-ray photons approaches 1 μm, as evidenced by a Monte Carlo simulation and actual x-ray intensity measurement as discussed below. If a lower voltage is used to reduce the generation depth, their L peaks have to be used. But these L peaks actually are merged as one big hump simply because the atomic numbers of these three elements are relatively small and close together, and the EDS energy resolution is limited.

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