RETRACTED ARTICLE: Monitoring the temperature through moving average control under uncertainty environment

Aslam, Muhammad; Shareef, Abdulmohsen Al; Khan, Khushnoor

doi:10.1038/s41598-020-69192-8

Cited by 15 publications

(5 citation statements)

References 35 publications

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“…MA is an unweighted moving average chart and is used for individual observations of conventional chart. This can be seen in the recent research conducted by Aslam et al (2020). They analysed issues related to monitoring the weather data.…”

Section: Literature Reviewmentioning

confidence: 99%

WITHDRAWN: Interval type-2 fuzzy moving average control charts considering explicit formula of average run length and their application

Razali

Abdullah

Ghani

et al. 2023

Preprint

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Previous literature suggest that fuzzy control charts are more sensitive than conventional one hence, it provides better quality and conformance of products. However, it is known that much of the data used in manufacturing sector cannot be expressed by type-1 fuzzy numbers and some of it more suitable to be expressed in type-2 fuzzy numbers. This paper aims to develop type-2 fuzzy moving average (MA) control charts by considering interval type 2 fuzzy numbers, and the case of known and unknown standard deviations. This new control chart combines the advantages of lower bound and upper bound of interval type-2 fuzzy numbers and a modified Best Nonfuzzy Performance as defuzzification method instead of typical centroid method, which can find the upper and lower control limits. In order to verify the performance of the proposed control chart, average run length (ARL) is computed and compared to other charts which are type-1 fuzzy MA chart and conventional MA chart. Twenty samples with sample size of six of fertilizers’ production is examined to identify the defects. Based on the result of the conventional MA chart, 8 out of 20 samples are “out of control”. On the other hand, type-1 fuzzy MA chart founds 10 samples are “out of control”, whereas interval type-2 fuzzy MA chart found 15 samples are “out of control”. Thus, we can conclude that, interval type-2 fuzzy chart is more sensitive and takes lesser number of observations to identify the shift in the process. In addition, the ARL test shows that interval type-2 fuzzy MA outperforms the other control charts under the comparison of ARL. Thanks to the introduction of interval type-2 fuzzy numbers to the MA and the explicit formula of ARL where the quality of fertilizers production can be improved.

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Section: Literature Reviewmentioning

confidence: 99%

WITHDRAWN: Interval type-2 fuzzy moving average control charts considering explicit formula of average run length and their application

Razali

Abdullah

Ghani

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…In addition, the present study can be extended for neutrosophic statistics [9,[29][30][31][32][33][34][35] as future research.…”

Section: Discussionmentioning

confidence: 94%

Ridge Fuzzy Regression Modelling for Solving Multicollinearity

Kim

Jung

2020

Mathematics

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This paper proposes an α-level estimation algorithm for ridge fuzzy regression modeling, addressing the multicollinearity phenomenon in the fuzzy linear regression setting. By incorporating α-levels in the estimation procedure, we are able to construct a fuzzy ridge estimator which does not depend on the distance between fuzzy numbers. An optimized α-level estimation algorithm is selected which minimizes the root mean squares for fuzzy data. Simulation experiments and an empirical study comparing the proposed ridge fuzzy regression with fuzzy linear regression is presented. Results show that the proposed model can control the effect of multicollinearity from moderate to extreme levels of correlation between covariates, across a wide spectrum of spreads for the fuzzy response.

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“…[32] used a neutrosophic soft matrix (NSM) and relative weights of experts to develop an algorithmic strategy for group decision making (GDM) challenges. [33] used neutrosophic statistics to examine data from diabetes patients who had undergone a new diagnosis test. [34] worked on the estimation of the ratio of a crisp variable and a neutrosophic variable and shown improvement over the classical ratio method of estimation.…”

Section: Estimation Under Neutrosophic Sampling Theorymentioning

confidence: 99%

Generalized Neutrosophic Sampling Strategy for Elevated Estimation of Population Mean

Yadav,

Smarandache

2024

SSRN Journal

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RETRACTED ARTICLE: Monitoring the temperature through moving average control under uncertainty environment

Cited by 15 publications

References 35 publications

WITHDRAWN: Interval type-2 fuzzy moving average control charts considering explicit formula of average run length and their application

WITHDRAWN: Interval type-2 fuzzy moving average control charts considering explicit formula of average run length and their application

Ridge Fuzzy Regression Modelling for Solving Multicollinearity

Generalized Neutrosophic Sampling Strategy for Elevated Estimation of Population Mean

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