一个基于相邻像素兼容度的模糊加权平均滤波器

在文献[1]的基础上，提出几个改进的模糊加权平均滤波器。本文的方案不仅同时考虑了相邻像素对中心像素的兼容性以及中心像素对相邻像素的兼容性，而且还考虑到了权系数对局部环境的适应性。实验结果表明，该方法相比文献[1]中的模糊加权平均滤波器以及标准的均值滤波器、中值滤波器在噪声消除与边缘保留方面具有更好的性能。     

滑坡相似材料试验结果优化分析研究

在运用模糊综合评判确定的滑坡相似材料试验配合比隶属度基础上，利用方差分析确定各因素的数学优化区间，结合变量有上下界的改进单纯形法，获得技术，经济上的最佳配合比，克服了统计优化理论不能在连续区间寻优的缺点，这对从事滑坡相似材料试验研究具有一定的实际意义。     

基于模糊事件概率理论的水质风险率计算方法

针对水环境系统的随机不确定性和模糊不确定性，分析了影响水环境中水质风险的不完善性和模糊性因素，将水环境中水质风险作为一个模糊事件，利用模糊事件概率理论，提出了水环境水质超标的模糊随机风险率计算模型。通过引入模糊事件信息熵来评价隶属函数特征值取值的可靠程度，定量描述了隶属函数特征值与风险率的关系，进而计算出风险率。实例计算结果证明了方法的有效性。     

Editorial.

Presents some brief remarks from the editor of the Journal of Educational Psychology regarding his goals for the Journal, and noting the decline in membership in Division 15. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Analytic methods for modeling longitudinal data from rolling therapy groups with membership turnover.

Interventions for a variety of emotional and behavioral problems are commonly delivered in the context of treatment groups, with many using rolling admission to sustain membership (i.e., admission, dropout, and discharge from group are perpetual and ongoing). The authors present an overview of the analytic challenges inherent in rolling group data and outline commonly used (but flawed) analytic and design approaches to addressing (or sidestepping) these issues. Moreover, the authors propose use of latent class pattern mixture models (LCPMMs) as a statistically and conceptually defensible approach for modeling treatment data from rolling groups. The LCPMM approach is illustrated with rolling group data from a group-based alcoholism pilot treatment trial (N = 128). Different inferences were made with regard to treatment efficacy under LCPMM vs. the commonly used standard group-clustered latent growth model (LGM); coupled with other preliminary findings in this area, inferences from LGMs may be overly liberal when applied to data from rolling groups. Continued work on data analytic difficulties in groups with membership turnover is critical for furthering the ecological validity of research on behavioral treatments. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

用基函数神经网络实现多阈值图象分割

本文介绍了一种用基函数神经网络实现多阈值图象分割的新方法。它从函数逼近的角度研究基于灰度直方图的多阈值分割问题，提出了一种模糊反向传播学习算法，采用该算法的高斯基函数网络能够准确检测直方图中包含的子区域和它们的分布函数，而且速度很快。实验表明本文的方法在实际图象分割中是有效的。     

Linear interpolation in a fuzzy information space

An approach to solving a linear interpolation problem in a fuzzy information space is proposed. Two different schemes of interpolation are outlined: a heuristic one, based on the geometrical interpretation of operations, and an optimization one, based on the expansion principle. The results obtained allow performing fuzzy linear prediction. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 2, pp. 55–68, March–April 2006.     

A new voltage control equipment using fuzzy inference

Power system control equipment needs higher sensitivity and operational reliability. Advanced voltage control equipment is needed for reducing the frequency of tap changes and improving the characteristics (the relationship between the actual voltage and reference voltage) of the voltage to meet today's power system requirements. However, these objectives are in a trade-off relationship. Studies of voltage control derived from a knowledge base suitable for electric power systems can satisfy these objectives using fuzzy inference. Compared with corresponding conventional equipment, the new equipment improved the deviation of 30 min average voltage of 30 percent. This paper describes the design concept of new voltage control equipment using fuzzy inference. In addition, field test results are described along with rules of fuzzy inference, membership functions, and the deviation of 30 min average voltage through detailed simulation.     

模糊综合评判方法在碳酸盐岩油气勘探中的应用

详细地阐述了模糊综合评判方法的数学原理及其在油气勘探开发中的应用.根据某油田的生产层参数资料,运用MICROSOFT EXCEL软件,在对各参数进行统计研究并了解它们分布规律的基础上,合理地构造出一系列隶属函数,通过编制相应的计算机程序,完成综合评判.评判结果与勘探实际吻合较好.该方法有效地适用于碳酸盐岩油气藏的勘探开发.     

一种基于遗传算法的模糊关联规则挖掘方法

文中提出了一种基于遗传算法的生成隶属度函数的方法,该方法通过遗传算法对初始种群进行优化,获得一个适应度较高的隶属度函数编码,然后再根据机场噪声数据的实际标准对优化后得到的隶属度函数进行修正,进而得到梯形分布的隶属度函数编码.最后通过得到的隶属度函数对数据进行模糊化,并采用FP-trees算法生成模糊关联规则.该文针对数量型属性提出了这种方法,它的优点是能够使通过遗传算法得到的较优的隶属度函数更加适用于实际的数据集.