Moti Schneider - Academia.edu (original) (raw)

Papers by Moti Schneider

Information Sciences, 1994

International Journal of Intelligent Systems, May 1, 2001

ABSTRACT This paper describes a new method that utilizes technology from soft computing to unders... more ABSTRACT This paper describes a new method that utilizes technology from soft computing to understand words after any OCR software system generated the proper database. First, the problem will be defined very precisely, and then, the algorithm for solving the problem of recognizing words will be presented. Finally, examples are provided to show how the algorithm is applied to recognize different types of words. © 2001 John Wiley & Sons, Inc.

Fuzzy Economic Review, 2003

Genetic algorithms have recently gained notoriety as search engines of remarkable power, successf... more Genetic algorithms have recently gained notoriety as search engines of remarkable power, successfully search-ing, in reasonably short times, spaces completely intractable to most traditio-nal methods. The application of the genetic algorithm to the difficult problem of fuzzy system optimization has revealed that they are capable of refining nearly every aspect of the fuzzy system, generating near-optimal con-trollers, which exceed the

Series in Machine Perception and Artificial Intelligence, 2005

Chapter 6 Clustering Algorithms for Variable-Length Vectors and Their Application to Detecting Te... more Chapter 6 Clustering Algorithms for Variable-Length Vectors and Their Application to Detecting Terrorist Activities Menahem Friedman Department of Physics, Nuclear Research ... 6.2 The similarity between an incoming vector v and a clus-ter C with centroid c is m (v) sim {v, c ...

This paper addresses some of the issues involved in developing a technology that supports the imp... more This paper addresses some of the issues involved in developing a technology that supports the implementation of an autonomous fuzzy hybrid intelligent systems. The technology is based on the premise that integrated solution architectures will be much more effective and highly flexible in their ability to successfully handle a broad base of applications with a wider scope of problem variations. Hybrid systems in artificial intelligence represent a new field of research that deals with the synergism of expert systems and neural network technologies. The integration of the computational paradigms of these two highly complementary knowledge representation techniques is imperative to the process of developing effective robust intelligent systems for a large number of important applications

Proceedings of the 1993 ACM/SIGAPP symposium on Applied computing states of the art and practice - SAC '93, 1993

Proceedings of the 1988 ACM SIGSMALL/PC symposium on ACTES - SIGSMALL '88, 1988

Mathematical and Computer Modelling, 2005

We present a new fuzzy timed Petri net model. Each transition firing in our model is associated w... more We present a new fuzzy timed Petri net model. Each transition firing in our model is associated with a fuzzy number; during transition, firings tokens are removed from input and added to output places. We consider the marks changing rate in each place as constant, and our performance analysis is based on the reachability state graph. Our model has fuzzy

International Journal of Intelligent Systems, 2003

ABSTRACT The basic operations of fuzzy sets, such as negation, intersection, and union, usually a... more ABSTRACT The basic operations of fuzzy sets, such as negation, intersection, and union, usually are computed by applying the one-complement, minimum, and maximum operators to the membership functions of fuzzy sets. However, different decision agents may have different perceptions for these fuzzy operations. In this article, the concept of parameterized fuzzy operators will be introduced. A parameter α will be used to represent the degree of softness. The variance of α captures the differences of decision agents' subjective attitudes and characteristics, which result in their differing perceptions. The defined parameterized fuzzy operators also should satisfy the axiomatic requirements for the traditional fuzzy operators. A learning algorithm will be proposed to obtain the parameter α given a set of training data for each agent. In this article, the proposed parameterized fuzzy operators will be used in individual decision-making problems. An example is given to show the concept and application of the parameterized fuzzy operators. © 2003 Wiley Periodicals, Inc.

International Journal of Intelligent Systems, 2001

Fuzzy Sets and Systems, 1988

... Addison-Wesley, Reading, MA (1985). [8]. MM Gupta, A. Kandel, W. Bandler and JB Kizka, Approx... more ... Addison-Wesley, Reading, MA (1985). [8]. MM Gupta, A. Kandel, W. Bandler and JB Kizka, Approximate Reasoning in Expert Systems. , North-Holland, Amsterdam (1985). [9]. M.Schneider, W. Bandler and A. Kandel, The FESIP Expert System. ...

IEEE International Conference on Systems, Man, and Cybernetics, 1988

ABSTRACT This paper demonstrates a mechanism for incorporating and independently evaluating membe... more ABSTRACT This paper demonstrates a mechanism for incorporating and independently evaluating membership functions and certainty factors during the preprocessing phrase in fuzzy expert systems. By providing this flexibility within the framework of a fuzzy expert system tool, the expert system becomes better equipped to model real-world control applications.

Proceedings of the 1993 Acm Sigapp Symposium on Applied Computing States of the Art and Practice, Mar 1, 1993

Data Mining and Knowledge Discovery Handbook, 2000

ABSTRACT In this chapter we describe some basic concepts from fuzzy logic and how their applicabi... more ABSTRACT In this chapter we describe some basic concepts from fuzzy logic and how their applicability to Data Mining. First we discuss some basic terms from fuzzy set theory and fuzzy logic. Then, we provide examples that show how fuzzy sets and fuzzy logic can be applied best to discover knowledge from a given database.

Fuzzy Sets and Systems, Aug 1, 1999

A new approach to fuzzy logic controllers is introduced. It is based on blending fuzzy logic with... more A new approach to fuzzy logic controllers is introduced. It is based on blending fuzzy logic with conventional robust linear control in order to avoid instability due to non-linear elements, reduce feedback control efforts and achieve desired closed-loop specifications, which are not achievable by linear-time-invariant (LTI) controllers. Backing up trucks is a well-known example whose model includes non-linearities and model

This chapter describes data mining in finance by discussing financial tasks, specifics of methodo... more This chapter describes data mining in finance by discussing financial tasks, specifics of methodologies and techniques in this data mining area. It includes time dependence, data selection, forecast horizon, measures of success, quality of patterns, hypothesis evaluation, problem ID, method profile, attribute-based and relational methodologies. The second part of the chapter discusses data mining models and practice in finance. It covers use of neural networks in portfolio management, design of interpretable trading rules and discovering money laundering schemes using decision rules and relational data mining methodology.