Showing papers on "Neuro-fuzzy published in 1984"
TL;DR: An algorithm for constructing models on the basis of fuzzy and nonfuzzy data with the aid of fuzzy discretization and clustering techniques is proposed.
524 citations
Book•
01 Jan 1984
TL;DR: [B95] Boman, M.
Abstract: [B95] Boman, M.: " Rational Decisions and Multi-Agent Systems " in Proc.
123 citations
TL;DR: A general query language, FRIL, which uses fuzzy base relations and rewrite rules is described and incorporates an automated fuzzy inference mechanism and should find applications in many areas of knowledge engineering such as expert systems, linguistic controllers, etc.
121 citations
TL;DR: It is suggested that by adopting some concepts from artificial intelligence, existing approaches to fuzzy control system design could be significantly enhanced.
79 citations
TL;DR: New approaches to unsupervised fuzzy classification of multidimensional data by using ‘semi-fuzzy’ or ‘soft’ clustering techniques to achieve this goal are discussed.
74 citations
01 Nov 1984
TL;DR: The concept of L2-stability and its graphical interpretation, i.e. the circle criterion, are used and the use of the classical Nyquist locus and the gain-phase chart are brought into the picture.
Abstract: A hybrid (fuzzy and nonfuzzy) design concept has been proposed for the linear single-input single-output (SISO) system associated with fuzzy logic controllers. In the present design techniques, the concept of L2-stability and its graphical interpretation, i.e. the circle criterion, are used. Thus the use of the classical Nyquist locus and the gain-phase chart are brought into the picture. The drawbacks of the L2-stability/circle criterion are indicated and overcome. In the present design technique, which is graphical in nature, the designer is given a feel for the system. Examples are provided to illustrate the application of hybrid controller's structure for the synthesis of the linear SISO system associated with the fuzzy logic controller.
57 citations
34 citations
TL;DR: A fuzzy network technique is proposed, in which among activity branches emanating from a node, a branch to be undertaken once the node is realized belongs to a fuzzy set; and the time required to complete an activity branch belongs toA fuzzy set.
29 citations
TL;DR: The determination of a family of fuzzy relations of the system is described in detail and several identification problems in fuzzy systems are considered by means of fuzzy relational equations.
17 citations
Journal Article•
TL;DR: Fuzzy sets and fuzzy logic are qualitatively described, and the way in which they operate is illustrated by an example of a fuzzy controller.
Abstract: Fuzzy sets and fuzzy logic are qualitatively described, and the way in which they operate is illustrated by an example of a fuzzy controller. The application of fuzzy concepts to expert systems and computer vision is also discussed.
14 citations
TL;DR: The algorithm selection process is formulated as a fuzzy decision-making problem and a fuzzy algorithm selection method is proposed and this method is applied to the guidance and control problem in a command and control system.
Abstract: Generally, various approaches, like optimization, stabilization, adaptation and so on, can be taken to solve a control problem. Thus, there exist several kinds of algorithms to solve a certain problem and each algorithm's characteristics depend on the approach to be taken. In the case that these algorithms are applied to practical system problems, it is necessary to examine the algorithms' effectiveness and select a suitable one among usable algorithms. On the other hand, in a man-machine system, a human operator occasionally selects the better one by use of his experimental knowhow or a priori information. But it is very difficult for the operator to make a good decision continuously in a real time system. In this paper, an on-line algorithm selection problem is considered. Firstly, the algorithm selection process is formulated as a fuzzy decision-making problem and a fuzzy algorithm selection method is proposed. Ifthen type rules are used to reason the effectiveness of the algorithms. A priori information and know-how is utilized in the reasoning rules. Secondly, this method is applied to the guidance and control problem in a command and control system. Finally, simulation is conducted to evaluate the effectiveness of the proposed method.
TL;DR: This formulation of Fuzzy Linear Programming (FLP) Problem with fuzzy coeffieients by the extension principle seems tractable and applicable to real world decision problem where human estimation is influential.
Abstract: FORMULATION OF FUZZY LINEAR PROGRAMMING PROBLEM BASED ON FUZZY OBJECTIVE FUNCTION Hideo TANAKA Hidetomo ICHlHASHI University of Osaka Prefecture University of Osaka Prefecture Kiyoji ASAI University of Osaka Prefecture This paper describes a formulation of Fuzzy Linear Programming (FLP) Problem with fuzzy coeffieients by the extension principle. An order relation among fuzzy sets is defined by fuzzy max which is defined through the extension principle. Mathematically speaking, it means that The constraints and the object are both fuzzified by fuzzy linear function. Two FLP problems are considered as follows: (i) Problem tA) is to decide the non-fuzzy solution x that maximizes t subject t t (ii) Problem ¥=c;:x to ~ ~ ~ and (B) is to decide the fuzzy solution x that maximizes t ¥=c~ subject to kI::t::.~t. This fuzzy solution means the possibility distribution of solution in the problem(B) . Two concepts of optimality are used as maximizing the fuzzy objective function in a whole sense of fuzzy SEt and minimizing its fuzziness. Since the FLP problem (A) takes the possibility distribution of coefficients into consideration, its solution is robust to the uncertainty of model, compared with the solution in conventional LP problem. The FLP problem (B) provides us with the possibility of solution which reflects the fuzziness of paramHers. This formulation can be used as a model of top level decision problem in a fuzzy environment. This approach seems tractable and applicable to thE! real world decision problem where human estimation is influential. Fuzzy sets are restricted to a class of trianguler membership functions. Owing to this simplification, the FLP problem can be turned into a conventional LP problem with twice numbers of constraints in the FLP problem. Numerical examples are discribed to explain our FLP problems. © 1984 The Operations Research Society of Japan
01 Dec 1984
TL;DR: A mathematical description of a fuzzy dynamic system will be developed; a systematic method to derive a fuzzy controller strategy from an underlying fuzzy system model using fuzzy inverse relations will be established.
Abstract: A mathematical description of a fuzzy dynamic system will be developed; a systematic method to derive a fuzzy controller strategy from an underlying fuzzy system model using fuzzy inverse relations will also be established. The theoretical development presented here enables the suboptimal Control of the fuzzy system. As an illustrative example, a fuzzy controller problem with a unit delay will be discussed in detail and the simulation results will be presented.
01 Jun 1984
TL;DR: Fuzzy set theory has a number of properties that make it suitable for formalizing the uncertain information upon which medical diagnosis and treatment is usually based, and it provides a linguistic approach with an excellent approximation to texts.
Abstract: Fuzzy set theory has a number of properties that make it suitable for formalizing the uncertain information upon which medical diagnosis and treatment is usually based.
Firstly, it allows us to define inexact medical entities as fuzzy sets. Secondly, it provides a linguistic approach with an excellent approximation to texts. Finally, fuzzy logic offers powerful reasoning methods capable of drawing approximate inferences.
These facts suggest that fuzzy set theory might be a suitable basis for the development of a computerized diagnosis and treatment-recommendation system. This is borne out by trials performed with the medical expert system CADIAG-2, which uses fuzzy set theory to formalize medical relationships.
TL;DR: Based on the experience of the operators in tuning the parameters of the widely used PI controller, a PI model reference fuzzy adaptive control system (MRFAC) is studied and the fuzzy control can be represented explicitly.
TL;DR: It is indicated that a design of the simple control algoritms based upon fuzzy approach leads to non-linear deterministic algorithms of the types P, I, PD and PI.
01 Jan 1984
TL;DR: The goal of this article is to study the basic pros and cons of engineering fuzzy simulation and to describe the main features of the programming system CONFUCIUS which has been used to solve more than hundred practical engineering tasks.
Abstract: Engineering science is fuzzy. Any technical operation under close look gives evidence supporting this statement. This is why a fuzzy model could be very useful however a practical analysis of industrial problems requires timeconsuming evaluation of multidimensional fuzzy relations. A development of suitable fuzzy software is inevitable. The goal of this article is to study the basic pros and cons of engineering fuzzy simulation and to describe the main features of the programming system CONFUCIUS which has been used to solve more than hundred practical engineering tasks.
01 Jan 1984
TL;DR: The theoretical development presented here enables the suboptimal control of the fuzzy system and a systematic method to derive a fuzzy controller Strategy from an underlying fuzzy system model using fuzzy inverse relations is established.
Abstract: A mathematical description of a fuzzy dynamic System Will be developed; a systematic method to derive a fuzzy controller Strategy from an underlying fuzzy system model using fuzzy inverse relations will also established. The theoretical development presented here enables the suboptimal control of the fuzzy system. an illustrative example, a fuzzy controller problem with a unit delay will be discussed in detail and the simulation results will be presented.
TL;DR: This paper is intended to provide a comprehensive survey of the increasing volume of literature to be found on Fuzzy Clustering methods and an introductory guide from a computing standpoint may prove helpful.
01 Sep 1984
TL;DR: It is shown that the fuzzy set theory of Zadeh offers a new perspective for modeling for humans thinking and language use and is assumed that real expert human operators of aircraft, power plants and other systems do not think of their control tasks or failure diagnosis tasks in terms of control laws in differential equation form, but rather keep in mind a set of rules of thumb in fuzzy form.
Abstract: Computer aids in expert systems were proposed to diagnose failures in complex systems. It is shown that the fuzzy set theory of Zadeh offers a new perspective for modeling for humans thinking and language use. It is assumed that real expert human operators of aircraft, power plants and other systems do not think of their control tasks or failure diagnosis tasks in terms of control laws in differential equation form, but rather keep in mind a set of rules of thumb in fuzzy form. Fuzzy set experiments are described.
TL;DR: Situational control is an effective means in the control of complex systems and its application to the problems of operative control of power systems and to the design control of robotic manufacturing lines has given promising results.