TOWARD A FUZZY MODEL OF POLISH INTERNET MORTGAGE MARKET

This article presents our continuing efforts to develop a model of the Internet-based mortgage market in Poland. It sums up modeling research done over the last 4 years, also showing the stages and the process of building and verifying the proposed model consisting of three submodels. The submodels are described for three market situations; that is, a stable market, financial crisis, and economic boom. The proposed model variables are analyzed statistically and the submodels are verified. The article presents the most current stage of model development and concludes with suggestions for further research in this area leading to the ultimate application of the proposed model in a real-life prognosis process.     

基于时态数据库的极小子结构逻辑系统

逻辑是知识表达的重要方法,但由于时序性知识与时间属性知识交叉应用的复杂性,其对时态数据库支撑一直不尽如人意.目前时态数据运算体系不完备,时态关系演算缺乏系统和有力的逻辑与代数理论支持.为此,文中从子结构逻辑出发,针对时态数据库及其信息处理中关键的知识推理、时态操作与函数依赖等内容,构建了一个极小的(最小的)子结构逻辑系统TDLrmin,其恰好等价于传统的数据库函数依赖Armstrong规则.TDLmin系统能在逻辑语义模型中对时序性、时间属性进行表达,而在句法逻辑系统将时间剥离,从而既表达了时态知识,对时态操作进行处理,又降低了逻辑系统的复杂度,使得逻辑系统的时间复杂度为P-time (O(n2)).而该逻辑系统还可与传统的Allen方法进行对接,使得相关时态查询所需的时间代价为传统非时态查询的时间加上一个复杂度仅为O(n)的线性时间,从而使得系统具有更强的普适性和应用前景.     

基于ECL逻辑器件的高频相移信号发生电路

提出了一种基于脉冲抑制原理的可编程ECL逻辑器件的高频相移信号发生电路。给出了输出相移量为2π/32的20 MHz信号的频率稳定性测试实验结果,对于1 s～10 000 s的积分时间,艾伦标准方差值σy(τ)<10-9。该电路具有电路设计原理简单、可复制性强、电路体积小、成本低等优点。     

Approximated fuzzy logic controlled shunt active power filter for improved power quality

Shunt active power filters have been widely used for power quality improvement. With the advancement in artificial intelligence techniques, the applications of fuzzy logic‐based control systems have increased manifolds. This paper proposes a reduced rule fuzzy logic controller (FLC) in the voltage control loop of a shunt active power filter (APF), which is approximating a conventional large rule FLC. The difference between the controlled outputs of two controllers is compensated by proposed compensating factors. The dynamic response and harmonic compensation performance of proposed 4‐rule approximated fuzzy logic controller (AFLC) is compared with 25‐rule FLC. A three‐phase shunt APF is used for harmonic and reactive power compensation. The proposed scheme is tested with randomly varying single and multiple non‐linear loads. The simulation results presented under transient and steady‐state conditions confirm that the proposed 4‐rule AFLC efficiently approximates the 25‐rule FLC. The proposed control methodology takes less computational time and computational memory as the numbers of rules are reduced significantly.     

AN APPROACH TO REASONING ABOUT HYBRID SYSTEMS

A formal approach is presented for proving temporal properties of dynamic systems. Its main advantage is that it can be used to prove properties of hybrid systems, i.e. those whose state contains both discrete and continuous parameters. In contrast, most current temporal reasoning techniques are restricted either to purely discrete systems or to purely continuous systems. Our approach is based upon a new modeling technique called DMOD. A DMOD model of a system defines the causality relation between events in the system, using definite clauses, i.e. logic programs. Thereby, the problem of reasoning about hybrid systems is reduced to one of reasoning about the behavior of definite clauses. As these possess a simple proof theory, reasoning is substantially simplified.     

Sup-t-norm and inf-residuum are a single type of relational equations

We show that the sup-t-norm and inf-residuum types of fuzzy relational equations, considered in the literature as two different types, are in fact two particular instances of a single, more general type of equations. We demonstrate that several pairs of corresponding results on the sup-t-norm and inf-residuum types of equations are simple consequences of single results regarding the more general type of equations. We also show that the new type of equations subsumes other types of equations such as equations with constraints on solutions, examples of which are fuzzy relational equations whose solutions are required to be crisp (ordinary) relations.     

A ROUGH SET/FUZZY LOGIC BASED DECISION MAKING SYSTEM FOR MEDICAL APPLICATIONS

Abstract

A method of performing prognostic modeling of disease states is proposed. The technique uses rough sets to extract rules from a database. The data is then reformatted into a fuzzy logic template, and a learning algorithm is used to adjust the fuzzy set membership functions. The method is applied to the POSCH problem, which looks at risk factors associated with the progression of coronary artery disease. The POSCH data has several shortcomings, including a limited number of cases, correlated inputs, as well as noise on both the inputs and outcome. The problem was to predict progression of atherosclerosis in the LAD three years after baseline based on physiologic data available at baseline. The proposed rough/fuzzy set method correctly predicted progression of atherosclerotic disease in 69% of the patients, which is statistically better than neural network, rough set and logistic models performed.     

Support vector machines for spatiotemporal tornado prediction

The use of support vector machines (SVMs) for predicting the location and time of tornadoes is presented. In this paper, we extend the work by Lakshmanan et al. (Proceedings of 2005 IEEE international joint conference on neural networks (Montreal, Canada), 3, 2005a, 1642–1647) to use a set of 33 storm days and introduce some variations that improve the results. The goal is to estimate the probability of a tornado event at a particular spatial location within a given time window. We utilize a least-squares methodology to estimate shear, quality control of radar reflectivity, morphological image processing to estimate gradients, fuzzy logic to generate compact measures of tornado possibility and SVM classification to generate the final spatiotemporal probability field. On the independent test set, this method achieves a Heidke's skill score of 0.60 and a critical success index of 0.45.     

THE LOGIC OF AUTOMATA

Automata are the prime example of general systems over discrete spaces, and yet the theory of automata is fragmentary and it is not clear what makes a general structure an automaton. This paper investigates the logical foundations of automata relating it to the semantics of our notions of uncertainty, state and state-determined. A single framework is established for the conventional spectrum of automata: deterministic, probabilistic, fuzzy, and non-deterministic, which shows this set to be, in some sense, complete. Counter-examples are then developed to show that this spectrum alone is inadequate to describe the behaviour of certain forms of uncertain system. Finally a general formulation is developed based on the fundamental semantics of our notion of a state that shows that the logical Structure of an automaton must be at least a positive ordered semiring. The role of probability logic, its relationship to fuzzy logic, the rotes of topological models of automata, and the symmetry between inputs and outputs in hyperstate/hyperinput-determinedsystems are also discussed.     

Fuzzy and simulation-based techniques for industrial safety and risk assessment

This paper characterizes the development of a hybrid computer-based tool supporting design for safety practices in industrial plant component specification and layout definition. The tool combines simulation and fuzzy logic techniques for the systematic risk assessment of specified design and layout configurations for plants dealing with hazardous materials. In the hybrid system architecture, the simulation module provides the historical experience for a priori hazard identification and ranking, accounting for the domino effects of possible accidental occurrences, while the fuzzy module provides the correlation matrices for concurrent hazard evaluation and overall risk assessment. In particular, the fuzzy module enables the quantitative assessment and comparison among alternative design solutions providing design guidelines, which can be further tested and verified through simulation.