The concept of neutrosophic statistics is applied to propose two monitoring schemes which are an improvement of the neutrosophic exponentially weighted moving average(NEWMA)chart.In this study,two control charts are d...The concept of neutrosophic statistics is applied to propose two monitoring schemes which are an improvement of the neutrosophic exponentially weighted moving average(NEWMA)chart.In this study,two control charts are designed under the uncertain environment or neutrosophic statistical interval system,when all observations are undermined,imprecise or fuzzy.These are termed neutrosophic double and triple exponentially weighted moving average(NDEWMA and NTEWMA)control charts.For the proficiency of the proposed chart,Monte Carlo simulations are used to calculate the run-length characteristics(such as average run length(ARL),standard deviation of the run length(SDRL),percentiles(P_(25),P_(50),P_(75)))of the proposed charts.The structures of the proposed control charts are more effective in detecting small shifts while these are comparable with the other existing charts in detecting moderate and large shifts.The simulation study and real-life implementations of the proposed charts show that the proposed NDEWMA and NTEWMA charts perform better in monitoring the process of road traffic crashes and electric engineering data as compared to the existing control charts.Therefore,the proposed charts will be helpful in minimizing the road accident and minimizing the defective products.Furthermore,the proposed charts are more acceptable and actual to apply in uncertain environment.展开更多
如何根据无线环境的变化实时选择一个可靠的发送速率,进而保证数据传输的可靠性是无线通信研究的热点。针对传统累积和平均法(Cumulative Sum Average,CUSUMA)由于计算机存储数据位数的有限性可能导致的数据值超过计算机最大数据类型表...如何根据无线环境的变化实时选择一个可靠的发送速率,进而保证数据传输的可靠性是无线通信研究的热点。针对传统累积和平均法(Cumulative Sum Average,CUSUMA)由于计算机存储数据位数的有限性可能导致的数据值超过计算机最大数据类型表示范围,进而造成统计数据丢失的问题,提出基于指数加权移动平均(Exponentially Weighted Moving Average,EWMA)算法,计算对应速率下的数据发送成功率,并根据计算出的成功率实现动态速率选择。该算法可用于解决通用平均值算法导致的因数据过大造成的统计数据丢失问题。展开更多
基金This work was funded by the Deanship of Scientific Research(DSR),King Abdulaziz University,JeddahThe authors,therefore,gratefully acknowledge the DSR technical and financial support.
文摘The concept of neutrosophic statistics is applied to propose two monitoring schemes which are an improvement of the neutrosophic exponentially weighted moving average(NEWMA)chart.In this study,two control charts are designed under the uncertain environment or neutrosophic statistical interval system,when all observations are undermined,imprecise or fuzzy.These are termed neutrosophic double and triple exponentially weighted moving average(NDEWMA and NTEWMA)control charts.For the proficiency of the proposed chart,Monte Carlo simulations are used to calculate the run-length characteristics(such as average run length(ARL),standard deviation of the run length(SDRL),percentiles(P_(25),P_(50),P_(75)))of the proposed charts.The structures of the proposed control charts are more effective in detecting small shifts while these are comparable with the other existing charts in detecting moderate and large shifts.The simulation study and real-life implementations of the proposed charts show that the proposed NDEWMA and NTEWMA charts perform better in monitoring the process of road traffic crashes and electric engineering data as compared to the existing control charts.Therefore,the proposed charts will be helpful in minimizing the road accident and minimizing the defective products.Furthermore,the proposed charts are more acceptable and actual to apply in uncertain environment.
