Bankruptcy prediction in banks and firms via statistical and intelligent techniques – A review

This paper presents a comprehensive review of the work done, during the 1968–2005, in the application of statistical and intelligent techniques to solve the bankruptcy prediction problem faced by banks and firms. The review is categorized by taking the type of technique applied to solve this problem as an important dimension. Accordingly, the papers are grouped in the following families of techniques: (i) statistical techniques, (ii) neural networks, (iii) case-based reasoning, (iv) decision trees, (iv) operational research, (v) evolutionary approaches, (vi) rough set based techniques, (vii) other techniques subsuming fuzzy logic, support vector machine and isotonic separation and (viii) soft computing subsuming seamless hybridization of all the above-mentioned techniques. Of particular significance is that in each paper, the review highlights the source of data sets, financial ratios used, country of origin, time line of study and the comparative performance of techniques in terms of prediction accuracy wherever available. The review also lists some important directions for future research.     

Analysis of critical paths in a project network with fuzzy activity times

This paper proposes an approach to critical path analysis for a project network with activity times being fuzzy numbers, in that the membership function of the fuzzy total duration time is constructed. The basic idea is based on the extension principle and linear programming formulation. A pair of linear programs parameterized by possibility level α is formulated to calculate the lower and upper bounds of the fuzzy total duration time at α. By enumerating different values of α, the membership function of the fuzzy total duration time is constructed, and the fuzzy critical paths are identified at the same time. Moreover, by applying the Yager ranking method, definitions of the most critical path and the relative degree of criticality of paths are developed; and these definitions are theoretically sound and easy to use in practice. Two examples with activity times being fuzzy numbers of L-R and L-L types discussed in previous studies are solved successfully to demonstrate the validity of the proposed approach. Since the total duration time is completely expressed by a membership function rather than by a crisp value, the fuzziness of activity times is conserved completely, and more information is provided for critical path analysis.     

A chi-square method for obtaining a priority vector from multiplicative and fuzzy preference relations

Decision makers (DMs)’ preferences on decision alternatives are often characterized by multiplicative or fuzzy preference relations. This paper proposes a chi-square method (CSM) for obtaining a priority vector from multiplicative and fuzzy preference relations. The proposed CSM can be used to obtain a priority vector from either a multiplicative preference relation (i.e. a pairwise comparison matrix) or a fuzzy preference relation or a group of multiplicative preference relations or a group of fuzzy preference relations or their mixtures. Theorems and algorithm about the CSM are developed. Three numerical examples are examined to illustrate the applications of the CSM and its advantages.     

Normal forms for fuzzy logics: a proof-theoretic approach

A method is described for obtaining conjunctive normal forms for logics using Gentzen-style rules possessing a special kind of strong invertibility. This method is then applied to a number of prominent fuzzy logics using hypersequent rules adapted from calculi defined in the literature. In particular, a normal form with simple McNaughton functions as literals is generated for ?ukasiewicz logic, and normal forms with simple implicational formulas as literals are obtained for Gödel logic, Product logic, and Cancellative hoop logic.     

Two storage inventory model with fuzzy deterioration over a random planning horizon

An inventory model for a deteriorating item with stock dependent demand is developed under two storage facilities over a random planning horizon, which is assumed to follow exponential distribution with known parameter. For crisp deterioration rate, the expected profit is derived and maximized via genetic algorithm (GA). On the other hand, when deterioration rate is imprecise then optimistic/pessimistic equivalent of fuzzy objective function is obtained using possibility/necessity measure of fuzzy event. Fuzzy simulation process is proposed to maximize the optimistic/pessimistic return and finally fuzzy simulation-based GA is developed to solve the model. The models are illustrated with some numerical data. Sensitivity analyses on expected profit function with respect to distribution parameter λ and confidence levels α₁ and α₂ are also presented.     

一类非仿射不确定非线性系统的自适应模糊输出反馈控制

针对一类非仿射的不确定非线性系统,利用H∞控制技术和模糊系统,提出一种基于观测器的混合的直接自适应模糊控制方法,该方法不需要系统的状态变量完全可测,同时取消了最优逼近误差平方可积的假设条件,而且跟踪误差渐近收敛到零。仿真结果表明所提设计方法的有效性。     

模糊信号码的一点注记

利用模糊信号码的代数性质给出了模糊信号码的一个充要条件:设A是字母表X上的一个模糊前缀码,那么A是模糊信号码当且仅当X*=T∪A0.∪P0.,这里P=AX-,T={u∈X*|X*uX*∩A0.=φ},满足条件T∩P0.=φ=T∩A0.,T■A0.X .同时讨论了一个模糊码满足X*A0.■A0.X*的一些等价条件,对最大模糊前缀码的性质也作了一些研究。     

基于单调包含度的模糊决策信息系统的知识约简

知识约简是机器学习,模式识别,信号处理等领域的主要问题之一。本文介绍了基于单调包含度的模糊决策信息系统的知识约简。证明了模糊决策信息系统的约简即是其对应信息系统的约简,从而为该种模糊决策信息系统的知识约简提供了简单直接的方法。     

Detection of functional states by the ‘LAMDA’ classification technique: application to a coagulation process in drinking water treatment

The present Note proposes a learning classification methodology to identify functional states on a coagulation process involved in drinking water treatment. In this work, we chose to carry out the supervised control of this process while using the LAMDA (Learning Algorithm for Multivariate Data Analysis) classification technique. The LAMDA classification technique proposes the interactive participation of the expert operator during the learning phase and in the optimisation of the classification. In this work, all information stemming from the environment process as well as expert knowledge has been aggregated and exploited. The application chosen for state identification is the Rocade drinking water treatment plant located at Marrakech, Morocco. To cite this article: B. Lamrini et al., C. R. Physique 6 (2005).     

连续论域上Fuzzy集的信息熵

在文献[1]的基础上,把模糊熵从离散论域推广到连续论域,给出连续论域上Fuzzy集的偏熵、关联熵等概念。对其主要性质进行讨论,取得了一些令人满意的结果。拓宽信息熵的研究领域,对不确定复杂系统的信息处理、知识学习、归纳学习、模糊信息学的进一步研究打下一定基础。