Examples of fuzzy

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As with the other systems, the fuzzy sets represent imprecise values of case attributes.
Furthermore, this simplicity of the induced knowledge coupled with a fuzzy linguistic representation makes the output particularly comprehensible.
However, there are certain differences that arise from the crisp or fuzzy nature of the induced knowledge, and these are highlighted where appropriate.
Since these solved instances can contain uncertain and imprecise values, linguistic values represented by fuzzy sets are used.
The main problem in this approach is to rank the crisp proposals according to the consumer's fuzzy constraints and preferences.
Furthermore, we distinguish between one-issue and multi-issue negotiation, and we consider crisp and fuzzy constraints on either negotiating side.
Take the standard, if somewhat fuzzy, definition of democracy as rule by the people.
The user is expected to describe their knowledge in terms of fuzzy sets and linguistic variables.
Section 4 introduces fuzzy systems and gives several examples.
We also need to be able to perform addition on fuzzy subsets.
The tighter the approximation we want, the less fuzzy the fuzzy subset is, and hence the smaller the base of the triangular fuzzy subset is.
Figure 9 shows all the membership functions of the fuzzy sets of the two inputs.
The fuzzy inference process is implemented using these rules.
We needed to design and train a fuzzy logic based affect recognizer that could recognize or "understand" the physiological responses of a person.
A group of fuzzy rules can be considered as a kind of combination of fuzzy predicates.
The reproduced photographs of the images of the man and the cat's eye view are quite remarkable, with the cat's eye view being fuzzy.
In order to prove the independence of d6, we propose an example inspired by the notion of fuzzy subset of a metric space.
With less than 60,000 words of training corpus, the fuzzy network model is superior to the probabilistic model.
Thus, we can say that the fuzzy network model is suited to estimating the membership functions under small training data.
Figure 1 shows the fuzzy network for the morphological analysis of the sentence.
Across languages, the boundaries across categories of morphology may become increasingly fuzzy and confusing.
The muddy symbolic mapping knowledge consists of fuzzy facts, fuzzy rules, and fuzzy procedures.
A fuzzy inference mechanism is used to query the knowledge base for problem solving.
Conceptual design generally consists of a search across an ill-defined space of possible solutions using fuzzy objective functions and vague concepts of the final structure.
Methods that manage uncertainty and/or impreciseness, such as fuzzy logic could be used to represent the uncertainty/impreciseness and make a crisp decision.
Lattice-based extensions of binary connectives to fuzzy connectives are presented.
We know that natural categories are fuzzy rather than nomothetic.
He originally tried to interpret the function as referring to a sort of fuzzy reality.
One of the key issues to emerge relates to the fuzzy boundary between neighbourliness and friendship on the hand, and ' care ' on the other.
In this research, a new fuzzy justification and evaluation method is proposed as follows.
In the following, fuzzy evaluation of assembly sequence will be discussed.
Based on the discussion above and other assembly knowledge, we can obtain many fuzzy rules to describe the effect of each parameter on assemblability.
Denoting these inputs as x and y, we use the following four-layer adaptive neuro-fuzzy inference system.
Design of a genetic-fuzzy system for planning crab gaits of a six-legged robot.
Learning to avoid moving obstacles optimally for mobile robots using a genetic-fuzzy approach.
A classified review on the combination fuzzy logic-genetic algorithms bibliography.
The same nouns also appeared in mass noun contexts preceded by the fuzzy quantifier much.
Consequently, the line between treatment of disease and enhancement-directed engineering seems itself to rely on a rather fuzzy distinction.
My preference is the latter, because it accounts realistically for the clearcut and fuzzy aspects of the data.
Even as it made the precise identity of styles unclear, the fuzzy use of terms increased their symbolic potency.
Obviously, there are measurability problems here, but that does not mean that a vague (or fuzzy) assessment cannot be made.
The neuro-fuzzy approach to modelling lettuce growth and greenhouse climate provides an interesting insight into time-dependent modelling.
Thus, we can build the conditional and fuzzy feature grammar.
Generally speaking, the biggest measure in the fuzzy set is the ultimate decision.
Several techniques are available to obtain these values, whether crisp or fuzzy.
Ranking engineering design concepts using a fuzzy outranking preference model.
Four th, the simple case study illustrated that the final outcomes are very sensitive to the constructs inherent in fuzzy set theory.
Simultaneous design of membership functions and rule sets for fuzzy controllers using genetic algorithms.
Genetic algorithm and singular value decomposition in the design of fuzzy systems for the modelling of explosive cutting process.
Identifying fuzzy rule-based models using or thogonal transformation and backpropagation.
The other is to represent fuzzy numbers by a finite number of a-level sets.
Four th, these rules are used to develop a fuzzy inference system.
Learning a coverage set of maximally general fuzzy rules by rough sets.
Hence, only one term in an output linguistic variable's term set can become a consequence of a fuzzy logic rule.
His research interests include database mining, fuzzy logic, robust design, and use of decision trees, regression trees, and genetic algorithms in off-line quality-control applications.
The fuzzy decision networks can be constructed from training patterns by machine learning techniques.
Automated analysis of mass spectral data using fuzzy logic classification.
Attainments for decision set are constituted by taking the minimum of attainments of three fuzzy goals per each via-point (equivalent to decision alternative).
Then the rule-adaptive fuzzy logic control algorithm is applied to the foot force controller.
The foot force sensor provides the force feedback for the real-time fuzzy logic force control.
Then we adopted an on-line rule-adaptive fuzzy logic control algorithm for walking machine leg control.
Other methods are learning control, neural network techniques18 and fuzzy control19,20 for robot force control.
In fuzzy logic there is no clear definition as to what is exactly true or false.
To overcome this difficulty, the paper proposes a force reflection gain-selecting algorithm based on neural network and fuzzy logic features.
The agents of the system are controlled using fuzzy control.
In this paper, an adaptive fuzzy sliding control is proposed and applied to a three-link passive manipulator.
The outputs of the fuzzy engine were the estimated valence and the estimated arousal.
Therefore, adaptive fuzzy control technique, being a model independent control paradigm for complex and uncertain systems, is a good choice for such systems.
In the direct adaptive fuzzy control, the fuzzy rules are directly incorporated into the controller itself.
Figure 5 demonstrates the block diagram of a fuzzy inference system.
Values in the table are adjusted to coincide efficiently with the fuzzy algorithm membership functions that are used to control the robot's input response.
In this paper, a fuzzy control system for a hexapod mobile robot navigating in unknown environments is presented.
The stability and convergence of the adaptive fuzzy sliding controller is proven both theoretically and practically by simulations.
However, in conventional fuzzy control design there is no well-defined method for them and often the design is done by trial and error.
The level of attainments for each fuzzy goal is indicated by its height in z-axis.
In ref. 2-4, robust adaptive fuzzy control methods are described.
There are also a few implementations of classical adaptive control and fuzzy-based control for hydraulic robot mechanism or similar applications.
With fuzzy reasoning, however, it is possible to obviate this estimation.
In other words, the universe of discourse of the equivalent scalar angle is divided into four fuzzy sets.
In such a case, fuzzy reasoning can prove invaluable in making the decision-making process resemble human reasoning.
Chapter 13 explores the representation of commonsense in the mathematical formalism of fuzzy logic.
Now we must admit to - - fuzzy boundaries between case markers and postpositions.
These examples are from corpora and from sources on the web. Any opinions in the examples do not represent the opinion of the Cambridge Dictionary editors or of Cambridge University Press or its licensors.