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。     

政府监管与企业加入第三方国际环境审计的模糊博弈分析

针对政府环境监管与企业实施环境行为博弈分析中无法对双方的损益情况做出判断的问题,文章结合三角模糊数构建了政府监管和企业加入第三方国际环境审计的博弈模型,分别指出了纯策略纳什均衡和混合策略均衡情况需要满足的条件,讨论了政府与污染环境企业博弈策略的影响因素及作用机制,为政府监管与企业加入第三方国际环境审计顺利实施提供了相关建议。然后通过三角结构元方法对算例进行求解,验证了结论的正确性和可行性,引入三角模糊概念更加符合实际应用情况,拓展了第三方国际环境审计的应用背景。研究结果表明,政府对消费者消费的引导和对污染企业的惩罚对企业是否决定加入第三方国际环境审计起着举足轻重的作用。     

非均匀分布下区间数排序可能度计算模型及其应用

区间数排序的可能度计算模型是学术界一直在不断探索的基础性问题之一。区间数刻画着事物属性特征的取值范围,以往学术界都假设在区间内的取值服从均匀分布。本文将均匀分布推广到一般分布,运用概率论的方法,构建了一个新的区间数排序的可能度计算模型,由此修正了以往关于两个区间数全等的定义,提出了区间数形等的概念,同时进一步修正了可能度的自反性条件和区间数的综合排序方法,并将理论应用于多属性决策问题,给出了基本的决策过程,通过实例决策问题的计算,呈现了新理论和新方法的可行性和合理性,具有很好的推广应用价值。     

基于模糊理论评估连续梁桥地震破坏状况

为了研究不同强度等级地震作用下连续梁桥的破坏模式及破坏程度,采用多级模糊综合评判方法建立连续梁桥的综合评估模型。根据连续梁桥的特点,利用连续梁桥各单元及各构件的破坏程度建立多个因素集,根据各因素的权重和评价标准,对多个因素集进行逐级评判,根据最大隶属度原则得到地震作用下连续梁桥的破坏情况,并通过等级参数评判法对不同地震强度下连续梁桥的破坏情况进行等级评判,得到连续梁桥破坏情况与地震强度之间的关系。最后,基于多级模糊综合评判方法对一座连续梁桥实例进行评判     

Indirect membership function assignment based on ordinal regression

In many fuzzy sets applications, fuzzy membership functions are commonly developed based on empirical or expert knowledge. The equation of a membership function is usually determined somewhat arbitrarily. This paper explores a novel membership function design method based on ordinal regression analysis. The estimated thresholds between ordinal measurement categories are applied to calculate the intersection points between fuzzy sets. These intersection points are further applied to determine the equations of the membership functions. Information distortion due to empirical guess can thus be reduced and more latent information in the fuzzy responses can therefore be captured. A case study investigating the relationship between foster mothers’ satisfaction and the foster time and information provided has been conducted in this research. The applicability and effectiveness of the proposed membership function assignment approach have been demonstrated through several case studies.