Optimal design of repetitive group sampling plans for Weibull and gamma distributions with applications and comparison to the Birnbaum–Saunders distribution

In this paper, we propose a multiple deferred state repetitive group sampling plan which is a new sampling plan developed by incorporating the features of both multiple deferred state sampling plan and repetitive group sampling plan, for assuring Weibull or gamma distributed mean life of the products. The quality of the product is represented by the ratio of true mean life and specified mean life of the products. Two points on the operating characteristic curve approach is used to determine the optimal parameters of the proposed plan. The plan parameters are determined by formulating an optimization problem for various combinations of producer's risk and consumer's risk for both distributions. The sensitivity analysis of the proposed plan is discussed. The implementation of the proposed plan is explained using real-life data and simulated data. The proposed plan under Weibull distribution is compared with the existing sampling plans. The average sample number (ASN) of the proposed plan and failure probability of the product are obtained under Weibull, gamma and Birnbaum–Saunders distributions for a specified value of shape parameter and compared with each other. In addition, a comparative study is made between the ASN of the proposed plan under Weibull and gamma distributions.     

机器学习视角下中国去产能产业的识别

随着中国环境压力的增加,政府提出了供给侧改革,去产能是改革的主要内容,但是由于产业特征的实时演变,需要对政策进行完善。文章运用模糊C均值算法和支持向量机算法分析现阶段需要进行去产能的产业,结果发现在现行去产能政策中大部分行业是需要去产能的,但煤炭开采和洗选业以及铁路、船舶、航空航天和其他运输设备制造业已不适合继续去产能,同时将化学原料和化学制品制造业加入去产能行列中。     

Multiplicative consistency analysis for interval fuzzy preference relations: A comparative study

To examine the multiplicative consistency of interval fuzzy preference relations (IFPRs), this paper first analyzes the limitations associated with the previous consistency concepts. Accordingly, a new consistency concept is defined that is an extension of the crisp case and overcomes limitations in the previous concepts. Next, a linear programming model to judge the consistency of IFPRs is constructed, and an approach to derive multiplicative consistent IFPRs is introduced. Furthermore, goal-programming models to determine missing values in an incomplete IFPR are constructed that have the highest consistent level with respect to known values. Moreover, a multiplicative consistency and consensus based method for group decision making with IFPRs is developed that can address incomplete and inconsistent cases. Finally, two practical decision-making problems are offered to demonstrate the feasibility and efficiency of the new method, and an analysis of a numerical and theoretical comparison with several related methods is performed.     

Missing value imputation method for disaster decision-making using K nearest neighbor

Due to destructiveness of natural disasters, restriction of disaster scenarios and some human causes, missing data usually occur in disaster decision-making problems. In order to estimate missing values of alternatives, this paper focuses on imputing heterogeneous attribute values of disaster based on an improved K nearest neighbor imputation (KNNI) method. Firstly, some definitions of trapezoidal fuzzy numbers (TFNs) are introduced and three types of attributes (i.e. linguistic term sets, intervals and real numbers) are converted to TFNs. Then the correlated degree model is utilized to extract related attributes to form instances that will be used in K nearest neighbor algorithm, and a novel KNNI method merging with correlated degree model is presented. Finally, an illustrative example is given to verify the proposed method and to demonstrate its feasibility and effectiveness.     

Comparison between method of moments and entropy regularization algorithm applied to parameter estimation for mixed-Weibull distribution

Mixed-Weibull distribution has been used to model a wide range of failure data sets, and in many practical situations the number of components in a mixture model is unknown. Thus, the parameter estimation of a mixed-Weibull distribution is considered and the important issue of how to determine the number of components is discussed. Two approaches are proposed to solve this problem. One is the method of moments and the other is a regularization type of fuzzy clustering algorithm. Finally, numerical examples and two real data sets are given to illustrate the features of the proposed approaches.     

中国商品流通现代化的模糊综合评价研究

完善了商品流通现代化指标体系,并运用模糊综合法将商品流通现代化指标转换成了指数。研究发现商品流通现代化水平与其区域位置、总体经济实力密切相关,且受到产业结构的影响。同时,通过基于指数的聚类分析得到如下结论:"率先发展型区域"要抓住历史机遇,培养创新型人才,保持领先地位;"积极追赶型区域"要发挥地理优势,打破省之间、行业和部门之间、所有制之间的界限,积极参与各种区域经济合作;"流通欠发达型区域"要进一步推进和实施西部大开发战略,推进物流现代化。     

Improving TAIEX forecasting using fuzzy time series with Box–Cox power transformation

Box–Cox together with our newly proposed transformation were implemented in three different real world empirical problems to alleviate noisy and the volatility effect of them. Consequently, a new domain was constructed. Subsequently, universe of discourse for transformed data was established and an approach for calculating effective length of the intervals was then proposed. Considering the steps above, the initial forecasts were performed using frequently used fuzzy time series (FTS) methods on transformed data. Final forecasts were retrieved from initial forecasted values by proper inverse operation. Comparisons of the results demonstrate that the proposed method produced more accurate forecasts compared with existing FTS on original data.     

乙二醇机组的温度模糊控制器设计与仿真

针对我国通信行业和计算机行业大型机房耗电量大的现状，提出了一种乙二醇机组控制系统。介绍了它的工作原理，阐述了它的总体控制方案，并重点阐述了采用温度模糊PID控制器对室内温度进行调节。仿真和实验结果表明：采用温度模糊控制器的系统运行稳定、可靠性高、节能效果明显，具有广阔的应用前景。     

基于模糊理论的城市快速路交通状态检测算法

通过分析流量、速度、占有率与城市快速路交通状态的关系,提出了一种基于模糊理论的城市快速路交通状态检测算法。通过在深圳市某快速路上的实际验证表明,该算法在能保证一定的检测率情况下,具有较低的误报率和较少的检测时间,表明此方法在实际应用中是切实可行的。