Determination of optimal chance double sampling plan using genetic algorithm

Sampath, S.; Deepa, S. N.

doi:10.3233/mas-130264

Cited by 6 publications

(7 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, the membership function of a fuzzy variable can also be specified by its credibility distribution. Without any doubts, credibility measure theory is applying to practical situations sucessfully, say, Peng and Liu [14] considered parallel machine scheduling problems with processing times, Zheng and Liu [24] studied a fuzzy vehicle routing optimization problem, Guo et al [2008] proposed credibility distribution grade kriging for investigation California State PM 10 spatial patterns, Wang et al [20,21] investigated a fuzzy inventory model without backordering, Sampath and Deepa [16] developed sampling plans containing fuzziness and randomness, and others. Nevertheless, the investigations in statistical estimation and hypothesis testing problems with fuzzy Comparisons of PM 2.5 between the years are difficult, due to "missing data" at sample sites [6,9].…”

Section: Fuzzy Theory and Membership Kriging Approachmentioning

confidence: 99%

Modelling PM2.5 with Fuzzy Exponential Membership

Guo¹

2015

Current Air Quality Issues

View full text Add to dashboard Cite

Air quality is a public and environmental issue that concerns people, whether in terms of global climate change or for health and the quality of life. The Environmental Protection Agency (EPA) regulates six primary air pollutants: Ozone, Particulate matter, Carbon Monoxide, Nitrogen Oxides, Sulfur Dioxide, and Lead [3]. Particulate matter (PM) refers to solid particles and liquid droplets found in air. Many manmade and natural sources produce PM directly, or produce pollutants that react in the atmosphere to form PM [9]. PM 2.5 are small particles or particulate matter, that are less than 2.5 micrometers in diameter. PM 2.5 can be produced by combustion from motor vehicles (esp. diesel powered buses and trucks), power plants, residential wood burning, forest fires, agricultural burning, and industrial processes [15]. They can also be formed in the air through when gases (air poullutants) and orgnaic compounds are transformed through chemical reactions. These tiny particles PM 2.5 can cause health hazards for people and also for the environment. People with heart diesease and lung problems including asthma, and also the elderly and children, are particularily vulnerable and at high risk when exposed to high levels of PM 2.5. Due to the tiny size of these PM 2.5 particles, they can penetrate to the deepest parts of the lungs, which is very dangerous to the human health. The California Air Resources Board (CARB) scentifically conducts studies and reports on the impacts of air pollutant exposures on public health, and the studies shows the negative impacts of PM 2.5 which is known to cause premature death [2]. Scientific studies has repeatedly found links between particulate matter and many health problems of people who has been exposed to high levels of PM 2.5 , including asthma, bronchitis, respiratory problems, including shortness of breath and painful breathing, and premature deaths [3]. One must also be aware of the effects of high levels of PM 2.5 on the environment as well. Since PM 2.5 are tiny, they can be carried by wind and travel great distances, so that it can cause

show abstract

Section: Fuzzy Theory and Membership Kriging Approachmentioning

confidence: 99%

Modelling PM2.5 with Fuzzy Exponential Membership

Guo¹

2015

Current Air Quality Issues

View full text Add to dashboard Cite

show abstract

“…The chance theory has been successfully used in designing single and double sampling plan for attributes by Sampath(2009) and Sampath and Deepa(2013). These sampling plans were based on Hybrid Binomial distribution studied by Sampath(2012).…”

Section: Chance Single Sampling Plan For Variablesmentioning

confidence: 99%

“…Tools of Fuzzy set theory become relevant for a given situation involving impreciseness. Designing of Fuzzy sampling plans have been considered by several researchers including Arnold(1996), Ohta and Ichihashi(1988), Kanagawa and Ohta(1990), Tamaki, Kanagawa and Ohta(1991), Grzegorzwski (1998Grzegorzwski ( ,2001Grzegorzwski ( ,2002, Hryniewicz(2008), Sampath(2009), Jamkhaneh, Sadeghpour and Yari(2011), Tong and Wang (2012), Sampath and Deepa(2013) etc. It is to be mentioned that majority of these works are related to sampling for attributes and they assume the presence of fuzziness in the parameters related to the underlying distributions.…”

Section: Introductionmentioning

confidence: 99%

“…To study the characteristics under imprecise situation Liu and Liu(2002) and Liu(2004) introduced a theory called Credibility theory parallel to fuzzy set theory. Sampath(2009) and Sampath and Deepa(2013) have applied Chance Theory in the theory of acceptance sampling for designing fuzzy acceptance sampling plan for attributes. In this paper, it is proposed to design the acceptance sampling plan for variables using the Chance Theory.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Chance Single Sampling Plan for Variables

Sampath

Madhavachari²,

Ramya

2015

International Journal of Fuzzy System Applications

View full text Add to dashboard Cite

This paper considers the design of single sampling plan for variables when the experimental values are treated as observations on independently and identically distributed normal random variables with fuzzy mean value. The design makes use of Liu's (2008) model IV of Chance Theory. Sampling Plans determined by the sample sizes and acceptance numbers are constructed for situations involving imprecise parameter on using chance theory. The process of determining sample sizes and acceptance threshold values has been carried out on assuming the observed values have hybrid normal distribution. Optimal chance sampling plans for variables are also determined by using minimum angle criterion for different choices of fuzzy risks.

show abstract

“…The usefulness of Credibility theory in data mining has been considered by Sampath and Vaidyanathan [18] and Sampath and Kalaivani [17] for dealing with fuzzy data. Applications of Credibility theory in fuzzy statistical quality control has been considered by Sampath [13] and Sampath and Deepa [16] for designing acceptance sampling plans for situations involving both fuzziness and randomness.…”

Section: Introductionmentioning

confidence: 99%

Credibility hypothesis testing of expectation of fuzzy normal distribution

Sampath

Ramya

2014

Journal of Intelligent &Amp; Fuzzy Systems

Self Cite

View full text Add to dashboard Cite

Identification of a suitable form for the membership function and assigning values for certain parameters in them while dealing with fuzzy environments is a challenging task in Credibility theory. Recently, Sampath and Ramya [15] considered a criterion called "membership ratio criterion" for testing the validity of a given hypothesis regarding the credibility distribution of a fuzzy variable against a rival hypothesis. A study on the application of the proposed criterion has been made with reference to the parameters involved in triangular credibility distributions. In this paper, a detailed study is made with reference to the fuzzy normal distribution. Test resulting from the application of membership ratio criterion for testing hypothesis about the expected value of the fuzzy normal distribution is considered assuming the variance of the distribution is known. Optimal properties of the derived tests are also studied.

show abstract

Determination of optimal chance double sampling plan using genetic algorithm

Cited by 6 publications

References 3 publications

Modelling PM2.5 with Fuzzy Exponential Membership

Modelling PM2.5 with Fuzzy Exponential Membership

Chance Single Sampling Plan for Variables

Credibility hypothesis testing of expectation of fuzzy normal distribution

Contact Info

Product

Resources

About