A fuzzy logic system based on Schweizer-Sklar t-norm

In recent years, the basic research of fuzzy logic and fuzzy reasoning is growing ac- tively day by day, such as the basic logic system BL proposed by Hajek[1]; fuzzy logic system MTL proposed by Esteva and Godo[2]; fuzzy reasoning, implication operators …     

Neural fuzzy logic programming

A foundational development of propositional fuzzy logic programs is presented. Fuzzy logic programs are structured knowledge bases including uncertainties in rules and facts. The precise specifications of uncertainties have a great influence on the performance of the knowledge base. It is shown how fuzzy logic programs can be transformed to neural networks, where adaptations of uncertainties in the knowledge base increase the reliability of the program and are carried out automatically.     

Intelligent e-learning system based on fuzzy logic

Neural Computing and Applications - In this technological world demanding latest updations in the domain knowledge, it is no surprise that e-learning has become a more viable option to a range of...     

A complementary fuzzy logic system

This article discusses complementary (C) fuzzy logic system that is one of continuous multiary logic systems that satisfies a complementary law differently from usual fuzzy logic systems. This article includes formulation of the C fuzzy logic system, derivation of tautologies, and mentions an example that typically shows a difference in inference computation between the C fuzzy logic system and a usual fuzzy logic system.     

Network forensics based on fuzzy logic and expert system

Network forensics is a research area that finds the malicious users by collecting and analyzing the intrusion or infringement evidence of computer crimes such as hacking. In the past, network forensics was only used by means of investigation. However, nowadays, due to the sharp increase of network traffic, not all the information captured or recorded will be useful for analysis or evidence. The existing methods and tools for network forensics show only simple results. The administrators have difficulty in analyzing the state of the damaged system without expert knowledge. Therefore, we need an effective and automated analyzing system for network forensics. In this paper, we firstly guarantee the evidence reliability as far as possible by collecting different forensic information of detection sensors. Secondly, we propose an approach based on fuzzy logic and expert system for network forensics that can analyze computer crimes in network environment and make digital evidences automatically. At the end of the paper, the experimental comparison results between our proposed method and other popular methods are presented. Experimental results show that the system can classify most kinds of attack types (91.5% correct classification rate on average) and provide analyzable and comprehensible information for forensic experts.     

基于模糊逻辑系统的输出跟踪控制问题

针对一类未知的非线性互联大系统，设计间接自适应模糊控制器以实现跟踪控制，采用模糊控制，模糊逻辑逼近和模糊滑模控制相结合的方法，对维数较低的子系统未知动态和维数较高的互联项未知动态分别采用两类模糊规则进行逼近，对系统的外部干扰及模糊逼近误差采用模糊滑模控制予以抵消，基于Lyapunov方法实现模糊系统中的参数自适应律并在线调节，所设计的间接自适应控制器使系统在Lyapunov意义下稳定，且跟踪误差趋近于0，仿真结果表明了该设计方法的正确性。     

A study of N-version programming and its impact on software availability

N-version programming is a useful approach to improve the quality of software, especially for safety-critical systems. Positive performance in enhancing software availability is an expected result. In this paper, a software availability model for the study of the impact of N-version programming technique is proposed and investigated. The characteristics of the N-version software system and its operation and failure process are analysed. Based on this analysis, the time-dependent behaviour of the software system, which alternates between online and offline states, is described using a Markov chain. This model derives quantitative measures of software availability. Numerical examples and comparisons are also presented in this paper to directly illustrate N-version programming's positive impact on software availability measures. N-version programming generally provides a positive impact on the system. However, it does not always guarantee a higher availability performance. General recommendations are provided on N-version software structure design based on cost-effective criteria.     

A fuzzy logic based multi-agents controller

This paper presents a fuzzy logic based controller (Multi-Agents System Controller (MASC)) which regulates the number of agents released to the network on a Multi-Agents Systems (MASs). A fuzzy logic (FL) model for the controller is as presented. The controller is a two-inputs-one-output system. The controllability is based on the network size (NTZ) and the available bandwidth (ABD) which are the inputs to the controller, the controller’s output is number of agents (ANG). The model was simulated using SIMULINK software. The simulation result is presented and it shows that ABD is the major constraint for the number of agents released to the network.     

Building a financial diagnosis system based on fuzzy logic production system

The purpose of this study is to build a financial expert system based on fuzzy theory and Fuzzy LOgic Production System (FLOPS), which is an expert tool for processing the ambiguity. The study consists if four parts. For the first part, the basic features of expert systems are presented. For the second part, fizzy concepts and the evaluation of classical expert systems to fuzzy expert systems will be presented. For the third part, the expert system shell (FLOPS) used in this study will be described. For the last part, it will be presented the financial diagnosis system, developed by using the Wall's seven ratios, traditional seven ratios and also 34 ratios selected by a financial expert. After analyzing and investigating these three kinds of methods, financial diagnosis system will be developed as a fuzzy expen system which used a membership function based on averages and standard deviation. At the last step, the new approach will be tried by increasing the fuzzy sets for five membership functions. Some practical examples will be given. Throughout the paper, the way of building a financial diagnosis system based on fuzzy expert system is stressed.     

A logic programming system for nonmonotonic reasoning

The evolution of logic programming semantics has included the introduction of a new explicit form of negation, beside the older implicit (or default) negation typical of logic programming. The richer language has been shown adequate for a spate of knowledge representation and reasoning forms.The widespread use of such extended programs requires the definition of a correct top-down querying mechanism, much as for Prolog wrt. normal programs. One purpose of this paper is to present and exploit a SLDNF-like derivation procedure, SLX, for programs with explicit negation under well-founded semantics (WFSX) and prove its soundness and completeness. (Its soundness wrt. the answer-sets semantics is also shown.) Our choice ofWFSX as the base semantics is justi-fied by the structural properties it enjoys, which are paramount for top-down query evaluation.Of course, introducing explicit negation requires dealing with contradiction. Consequently, we allow for contradiction to appear, and show moreover how it can be removed by freely changing the truth-values of some subset of a set of predefined revisable literals. To achieve this, we introduce a paraconsistent version ofWFSX, WFSX _p , that allows contradictions and for which our SLX top-down procedure is proven correct as well.This procedure can be used to detect the existence of pairs of complementary literals inWESX _p simply by detecting the violation of integrity rulesf L, -L introduced for eachL in the language of the program. Furthermore, integrity constraints of a more general form are allowed, whose violation can likewise be detected by SLX.Removal of contradiction or integrity violation is accomplished by a variant of the SLX procedure that collects, in a formula, the alternative combinations of revisable literals' truth-values that ensure the said removal. The formulas, after simplification, can then be satisfied by a number of truth-values changes in the revisable, among true, false, and undefined. A notion of minimal change is defined as well that establishes a closeness relation between a program and its revisions. Forthwith, the changes can be enforced by introducing or deleting program rules for the revisable literals.To illustrate the usefulness and originality of our framework, we applied it to obtain a novel logic programming approach, and results, in declarative debugging and model-based diagnosis problems.     

Matlab与C混合编程实现Type-2模糊系统

Type-2模糊系统的理论有着广泛的应用,但是Type-2模糊系统结构较Type-1模糊系统复杂,且编程实现难度和计算强度都较大.Matlab平台下,运用M语言调试算法,在实现Type-2模糊系统的基础上,利用C语言的高效性优化算法,改进程序,克服了Matlab计算瓶颈的问题.给出的Matlab C混合编程实现Type-2模糊系统的程序,编译后可以函数的形式调用,既保留了Matlab平台处理数据的便捷性,又具有很高的执行效率.仿真结果表明该方法的有效性.     

Set based logic programming

In a previous paper (Blair et al. 2001), the authors showed that the mechanism underlying Logic Programming can be extended to handle the situation where the atoms are interpreted as subsets of a given space X. The view of a logic program as a one-step consequence operator along with the concepts of supported and stable model can be transferred to such situations. In this paper, we show that we can further extend this paradigm by creating a new one-step consequence operator by composing the old one-step consequence operator with a monotonic idempotent operator (miop) in the space of all subsets of X, 2 ^X . We call this extension set based logic programming. We show that such a set based formalism for logic programming naturally supports a variety of options. For example, if the underlying space has a topology, one can insist that the new one-step consequence operator always produces a closed set or always produces an open set. The flexibility inherent in the semantics of set based logic programs is due to both the range of natural choices available for specifying the semantics of negation, as well as the role of monotonic idempotent operators (miops) as parameters in the semantics. This leads to a natural type of polymorphism for logic programming, i.e. the same logic program can produce a variety of outcomes depending on the miop associated with the semantics. We develop a general framework for set based programming involving miops. Among the applications, we obtain integer-based representations of real continuous functions as stable models of a set based logic program.      

基于遗传算法的模糊逻辑系统滚动学习方法

基于遗传算法的模糊逻辑系统滚动学习方法是一种局部优化策略，它针对参数空间内的局部区域，由区域内输入输出数据对提取模糊规则，并对规则参数进行调整，参数学习采用差分进行化算法，采用既包含区域内数据，又包含区域外数据的滚动数据窗技术，保证对局部模糊规则的参数调节不致影响系统在相邻区域的逼近性能，算法在保证精度的前提下大大减少了计算量，使遗传算法能应用于模糊逻辑系统的在线学习。     

非单点模糊逻辑系统在非线性信道均衡中的应用

提出一种新的基于非单点模糊逻辑系统的自适应模糊滤波器的设计方法，研究和对比了自适应非单点模糊滤波器在非线性数字通信信道均衡中的应用，仿真结果表明，基于非单点模糊逻辑系统的信道均衡器能够有效地遏制信道的时变性和随机噪声干扰，可有效地解决数字信道的非线性畸变问题；从提高数字通信信道的传输正确率和传输效率来说，具有较强的适应能力。     

A logic programming language based on the Andorra model

The Andorra model is a parallel execution model of logic programs which exploits the dependent and-parallelism and or-parallelism inherent in logic programming. We present a flat subset of a language based on the Andorra model, henceforth called Andorra Prolog, that is intended to subsume both Prolog and the committed choice languages. Flat Andorra, in addition todon’t know anddon’t care nondeterminism, supports control of or-parallel split, synchronisation on variables, and selection of clauses. We show the operational semantics of the language, and its applicability in the domain of committed choice languages. As an examples of the expressiveness of the language, we describe a method for communication between objects by time-stamped messages, which is suitable for expressing distributed discrete event simulation applications. This method depends critically on the ability to expressdon’t know nondeterminism and thus cannot easily be expressed in a committed choice language.     

A fuzzy clustering algorithm based on evolutionary programming

In this paper, a fuzzy clustering method based on evolutionary programming (EPFCM) is proposed. The algorithm benefits from the global search strategy of evolutionary programming, to improve fuzzy c-means algorithm (FCM). The cluster validity can be measured by some cluster validity indices. To increase the convergence speed of the algorithm, we exploit the modified algorithm to change the number of cluster centers dynamically. Experiments demonstrate EPFCM can find the proper number of clusters, and the result of clustering does not depend critically on the choice of the initial cluster centers. The probability of trapping into the local optima will be very lower than FCM.     

A fuzzy logic system for channel equalization

We present a new method for channel equalization using fuzzy logic. The membership functions are derived from the training data set, and a method to estimate the delay of the communication channel is proposed. The performance of the fuzzy equalizer is compared with that of a transversal filter equalizer. It is shown using simulations that the transversal filter requires a much larger training set to achieve the same error rate. It is also shown, using simulations, that the fuzzy equalizer performs better in the presence of channel nonlinearities     

基于模糊逻辑的多跳WSNs分簇算法

针对无线传感器网络节点能量消耗不均衡和网络寿命过短的问题,提出一种基于模糊逻辑的多跳WSNs分簇算法(FLCMN).该算法综合考虑节点剩余能量、节点邻居个数、邻居节点的平均剩余能量.根据预先设定模糊规则库,利用模糊系统评估出当选簇头的满意度.额外考虑邻居节点平均剩余能量,改善了簇内热点问题,均衡了簇内能量的消耗;同时,为了改善簇间热点问题,提出一种基于斐波那契序列的多跳传输方式,延长了网络的生存时间.通过仿真验证,FLCAMN算法在网络生存时间和能量消耗方面的性能都优于LEACH、EAMMH和DFLC算法.     

Bio-inspired fuzzy logic based tuning of power system stabilizer

In this paper, bacteria foraging optimization (BFO) – a bio-inspired technique, is utilized to tune the parameters of both single-input and dual-input power system stabilizers (PSSs). Conventional PSS (CPSS) and the three dual-input IEEE PSSs (PSS2B, PSS3B, and PSS4B) are optimally tuned to obtain the optimal transient performances. A comparative performance study of these four variants of PSSs is also made. It is revealed that the transient performance of dual-input PSS is better than single-input PSS. It is, further, explored that among dual-input PSSs, PSS3B offers superior transient performance. A comparison between the results of the BFO and that of genetic algorithm (GA) is conducted in this study. The comparison reveals that BFO is more effective than GA in finding the optimal transient performance. For on-line, off-nominal operating conditions Sugeno fuzzy logic (SFL) based approach is adopted. On real time measurements of system operating conditions, SFL adaptively and very fast yields on-line, off-nominal optimal stabilizer parameters.