A note on inverses in arithmetic with fuzzy numbers

Algorithms for systematical search of inverse in arithmetic operations with fuzzy numbers are discussed. The fuzzy number derived is considered either in a discrete representation of its support or described by the parameters of the corresponding membership function formula. Both algorithms are easy to be programmed for desk calculators.     

Optimisation of fault-tolerant fabric-cutting schedules using genetic algorithms and fuzzy set theory

In apparel industry, manufacturers developed standard allowed minutes (SAMs) databases on various manufacturing operations in order to facilitate better scheduling, while effective production schedules ensure smoothness of downstream operations. As apparel manufacturing environment is fuzzy and dynamic, rigid production schedules based on SAMs become futile in the presence of any uncertainty. In this paper, a fuzzification scheme is proposed to fuzzify the static standard time so as to incorporate some uncertainties, in terms of both job-specific and human related factors, into the fabric-cutting scheduling problem. A genetic optimisation procedure is also proposed to search for fault-tolerant schedules using genetic algorithms, such that makespan and scheduling uncertainties are minimised. Two sets of real production data were collected to validate the proposed method. Experimental results indicate that the genetically optimised fault-tolerant schedules not only improve the operation performance but also minimise the scheduling risks.     

Fuzzy Model of Regional Economic Competitiveness in GIS Spatial Analysis: Case Study of Gansu, Western China

After more than 20 years of impressive development since the economic reforms in 1978, today western China is facing an increasing development gap between its regions, particularly between urban and rural areas. Using the fuzzy comprehensive evaluation model, this paper aims to demonstrate the evolution of the economic competitiveness levels base on two categories of geographical unity in the province of Gansu located in Northwest China between 2000 and 2004. The results of fuzzy modeling are integrated into GIS spatiotemporal analyses in order to identify the spatial variation of each significant change in terms of the regional economic development. Our research effectively illustrates that there is a particular spatial dynamic of the economic development from region to region. Although the cities have improved very well in their economic competitiveness, the rural areas and minority regions still have a lot of progress to be achieved.     

Measurability criteria for fuzzy random vectors

Fuzzy random vector is a measurable map from a probability space to a collection of fuzzy vectors. Our aim in this paper is to discuss the measurability criteria for fuzzy random vectors, and show that under mild assumption, the measurability criteria for upper semicontinuous fuzzy random vectors can be expressed in several different but equivalent formulations. Finally, applying the obtained results, we resolve an open problem about the relationship between fuzzy random vectors and fuzzy random variables.     

Feature Selection using Fuzzy Support Vector Machines

The feature selection consists of obtaining a subset of these features to optimally realize the task without the irrelevant ones. Since it can provide faster and cost-effective learning machines and also improve the prediction performance of the predictors, it is a crucial step in machine learning. The feature selection methods using support machines have obtained satisfactory results, but the noises and outliers often reduce the performance. In this paper, we propose a feature selection approach using fuzzy support vector machines and compare it with the previous work, the results of experiments on the UCI data sets show that feature selection using fuzzy SVM obtains better results than using SVM.     

Fuzzy矩阵方程的摄动问题

讨论了Fuzzy矩阵A的同解简化矩阵A^(2)，指出陈贻源论文《解Fuzzy关系方程》中定量3的错误。研究Fuzzy矩阵方程的摄动问题，解决了汤服成（2000）提出的未解决问题。     

基于模糊聚类的语音识别

指出模糊聚类方法影响语间识别的正确率 ,提出用基于分解构造的模糊聚类方法设立语音模式的参考向量 ,说明该方法能提高语章识别的正确率。     

B—模糊集合代数和广义互信息公式

基于两种概率的区分，推导出了一个广义Shannon熵公式和一个广义互信息公式。后者和模糊性有关，并且柯用于语言和感觉中的信息度量。为了由原子语句为真的条件概率求出合语句为真的条件概率，提出了一个遵循存尔运算的模糊集合代数。所谓的模糊信息被还原为概率信息。新的理论在经典理论－概率论，集合论及Shannon信息论－的基础上容易理解。