The Karnik-Mendel (KM) algorithms are iterative procedures widely used in fuzzy logic theory. They are known to converge monotonically and superexponentially fast; however, several (usually two to six) iterations are still needed before convergence occurs. Methods to reduce their computational cost are proposed in this paper. Extensive simulations show that, on average, the enhanced KM algorithms can save about two iterations, which corresponds to more than a 39% reduction in computation time. An additional (at least) 23% computational cost can be saved if no sorting of the inputs is needed.

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Enhanced Karnik--Mendel Algorithms

This chapter is an overview of past and present works dealing with fuzzy intervals and their operations. A fuzzy interval is a fuzzy set in the real line whose level-cuts are intervals. Particular cases include usual real numbers and intervals. Usual operations on the real line canonically extend to operations between fuzzy quantities, thus extending the usual interval (or error) analysis to membership functions. What is obtained is a counterpart of random variable calculus, but where, contrary to the latter case, there is no compensation between variables. Many results pertaining to basic properties of fuzzy interval analysis are summed up in the chapter. Computational methods are presented, exact or approximate ones, based on parametric representations, or level-cut approximations. The generalized fuzzy variable calculus involving interactive variables is also discussed with emphasis on triangular-norm based fuzzy additions. Dual ‘optimistic’ operations on fuzzy intervals, i.e., with maximal error compensation are also presented; its interest lies in providing tools for solving fuzzy interval equations. This chapter also contains a reasoned survey of methods for comparing and ranking fuzzy intervals. The chapter includes some historical background, as well as pointers to applications in mathematics and engineering.

Fuzzy Interval Analysis

We tested the effects of innovation and market complexity on firm performance. Generational technological change—a major advance within a technology regime—fosters the emergence of niches and local...

https://www.jstor.org/stable/pdfplus/256996.pdf

Generational Technological Change: Effects of Innovation and Local Rivalry on Performance

Intrusion detection has gain a broad attention and become a fertile field for several researches, and still being the subject of widespread interest by researchers. The intrusion detection community still confronts difficult problems even after many years of research. Reducing the large number of false alerts during the process of detecting unknown attack patterns remains unresolved problem. However, several research results recently have shown that there are potential solutions to this problem. Anomaly detection is a key issue of intrusion detection in which perturbations of normal behavior indicates a presence of intended or unintended induced attacks, faults, defects and others. This paper presents an overview of research directions for applying supervised and unsupervised methods for managing the problem of anomaly detection. The references cited will cover the major theoretical issues, guiding the researcher in interesting research directions.

/pdf/machine-learning-techniques-for-anomaly-detection-an-2gpkeyiov5.pdf

Machine Learning Techniques for Anomaly Detection: An Overview

We study concept lattices with hedges. The principal aim is to control, in a parametrical way, the size of a concept lattice. The paper presents theoretical insight, comments, and examples. We show that a concept lattice with hedges is indeed a complete lattice which is isomorphic to an ordinary concept lattice. We describe the isomorphism and its inverse. These mappings serve as translation procedures. As a consequence, we obtain a theorem characterizing the structure of concept lattices with hedges which generalizes the so-called main theorem of concept lattices. Furthermore, the isomorphism and its inverse enable us to compute a concept lattice with hedges using algorithms for ordinary concept lattices. Further insight is provided in case one uses hedges only for attributes. We demonstrate by experiments that the size reduction using hedges as a parameter is smooth

http://phoebe.inf.upol.cz/~havrlanl/articles/BeVy_Rsfclh.pdf

Reducing the Size of Fuzzy Concept Lattices by Hedges

IEEE International Conference on Fuzzy Systems

1 Introduction 2 8086 Architecture 3 Assembler Language Programming 4 Modular Programming 5 Byte and String Manipulation 6 I/O Programming 7 Introduction to Multiprogramming 8 System Bus Structure 9 I/O Interfaces 10 Semiconductor Memory 11 Multiprocessor Configuration 12 VLSI Processing and Supporting Devices 13 The 80286/80287 Appendix: 8086/8088 Instruction Set Summary Index

Microcomputer Systems; The 8086-8088 Family Architecture, Programming and Design

Fast implementations of fuzzy arithmetic operations using fast Fourier transform (FFT)

By considering the infrared transmittance model of Zachor as the equation for an elliptic cone, a quadratic generalization is proposed that yields significantly greater computational accuracy. The strong-band parameters are obtained by iterative nonlinear, curve-fitting methods using a digital computer. The remaining parameters are determined with a linear least-squares technique and a weighting function that yields better results than the one adopted by Zachor. The model is applied to CO2 over intervals of 50 cm−1 between 550 cm−1 and 9150 cm−1 and to water vapor over similar intervals between 1050 cm−1 and 9950 cm−1, with mean rms deviations from the original data being 2.30 × 10−3 and 1.83 × 10−3, respectively.

Glenn A. Gibson

Papers

IEEE International Conference on Fuzzy Systems

Microcomputer Systems; The 8086-8088 Family Architecture, Programming and Design

Fast implementations of fuzzy arithmetic operations using fast Fourier transform (FFT)

Accurate Formula for Gaseous Transmittance in the Infrared

Microcomputers for engineers and scientists