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The past three years have witnessed a significant increase in the rate of growth of MIQ (Machine Intelligence Quotient) of consumer products and industrial systems. There are many factors which account for the increase in question but the most prominent among them is the rapidly growing use of soft computing and especially fuzzy logic in the conception and design of intelligent systems. ...
The method of context formalization based on fuzzy sets theory is suggested. This leads to the development of contextual systems for flexible decision-making in fuzzy environments. Contextual systems have the following features: automatic knowledge generation; knowledge interpretation and translation from one context to another; knowledge adaptation; problem solving...
By this paper we first try to determine the reasons for which Fuzzy Set Theory does not comply satisfactory with the expectations of cognitive psychologists. Then, by utilising results whose achievement was treated in earlier papers, it is reported of an attempt to provide for such purpose. To illustrate the presented development and the achieved results, a detailed paradigmatic example is reported.
First, we make some remarks concerning the definition of connectives in fuzzy logic. We point out possible disadvantages of considering exclusively t-norms and t-conorms as proper models for the conjunction and disjunction. Coincidence of S- and R-implications is investigated by solving functional equations for conjunctions. Then, we suggest a constructive approach to axiomatics of the generalized...
A formal logical systems dealing both with uncertainty (possibility) and vagueness (fuzziness) is investigated. It is many-valued and modal. The system is related to a many-valued tense logic. A completeness theorem is exhibited.
Fuzzy controllers are designed to work with knowledge in the form of linguistic control rules. But the translation of these linguistic rules into the framework of fuzzy set theory depends on the choice of certain parameters, for which no formal method is known. The optimization of these parameters can be carried out by neural networks, which are designed to learn from training data, but which are...
In this paper, a reinforcement learning algorithm is presented which is used to implement a fuzzy controller model for a given control problem based on the concept of ‘safety’. A concept of ‘safety’ is postulated and learned iteratively. It embodies the notion of cost as well as performance. The fuzzy controller model which is based on this notion of safety is closely related to the controllability...
This paper introduces a new method combining Fuzzy Logic and Genetic Algorithms to allow Intelligent Tutoring Systems to be efficient. We consider supervised teaching where the teacher assigns a initial profile and a finale profile to each student before starting the teaching. The system computes an optimal strategy which represents a way of evolving the student's knowledge from the initial profile...
This paper presents Neural Network and Genetic Algorithm approaches to fuzzy system design, which aims to shorten development time and increase system performance. An approach that uses neural network to represent multi-dimensional nonlinear membership functions and an approach to tune membership function parameters are given. A genetic algorithm approach that integrates and automates three fuzzy...
The problem of extracting information issued from several sources of information turns out to be a very important issue in intelligent systems. This problem is always encountered in multiexpert systems. In the field of remote sensing and geographic information system, this question is well known. Satellite images, geographic and geologic data, and expert knowledge can appear independent but,...
In this paper we propose an approach to consensus reaching based on linguistically expressed individual opinions and on so-called opinion changing aversion. We operate within this basic context: there is a group of experts which must choose a preferred alternative from a finite set of admissible ones according to several criteria. Each expert is called upon evaluate linguistically the alternatives...
In this paper is analysed, whether and how the proceeding commonly usued in Fuzzy Control can be transformed to non-technical expert systems. The new ideas are explained by means of a system for checking the creditability of small business firms.
To refine lateral control in an autonomous vehicle, a number of fuzzy controllers were developed in real-time simulation trials using real-world video images. The controller with the best results from the simulation trials was then mounted on the experimental vehicle ATHENE and shown to be functionally sound under the real-world circumstances of letting it drive through a corridor. The results were...
Conventional Robot Motion Coordination is usually based on the tasks of path planning, coordinate transformation and the solution of the inverse kinematic problem. This concept is widely used in industrial applications, where pre-determined paths have to be accurately followed (cartesian path planning) or a Point To Point movement is to be executed without considering any defined cartesian path (high...
Active magnetic bearings are used in applications where ordinary bearings meet difficulties. Due to nonlinear structure of active magnetic bearing system fuzzy logic control gives an attractive choice to control these systems. In this paper a fuzzy derivate gain adjusting method for active magnetic bearing control is presented. The method is based on the error and error derivate signals that are used...
This paper presents a fuzzy adaptive control technique to automate the dialysis procedure. The main points of this research are: use of a data base of fuzzy inference rules to formalize the medical experience, use of pre-processed lookup tables to speed up the computation and to allow for run-time changes of the inference rules, implementation of adaptive concept by means a set of performance tables,...
The statement advocated here is that a trainable scheme resembling some elements of physician's decision making process could lead to an increased classification accuracy. Problems are considered which are difficult to cope with from both pattern recognition and AI point of view. A combination scheme is proposed which consists of an AI preprocessing part and a pattern recognition part delivering the...
The task to solve is the automatic “safe” guidance of an autonomous mobile vehicle along a German highway (AUTOBAHN) at moderate to high speed. To assist the necessary decision making process of how to behave “safely” in an actual traffic situation, data about the road itself (e.g. number of lanes, lane width, lane markings), traffic signs and other traffic participants around the own car have to...
The paper presents a model of a fuzzy car distance controller. In contrast to conventional distance controllers this model additionally takes into account fuzzy information about the driver and about the environment. First the principle of the sharp car distance controller and its deficits are explained. The analysis shows that fuzzy models of the driver and of the environment are necessary to improve...
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