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Between Truth and Falsity
Between Truth and Falsity

... Real philosophers have gradually come to understand that most of our concepts are fuzzy. Some are fuzzier than others, but only mathematical and logical concepts seem completely to escape the fuzzy factor. Almost any other concept C you think of will admit of cases that cannot be unambiguously resol ...
The Archimedean Assumption in Fuzzy Set Theory
The Archimedean Assumption in Fuzzy Set Theory

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Artificial Intelligent Application to Power System Protection
Artificial Intelligent Application to Power System Protection

... operation and the dependability (no missing operations) requirements. The more secure is the relay (both the algorithm and its particular settings), the more it tends to misoperate or operate slowly. And vice versa, the faster is the relay, the more it tends to operate falsely. The problems listed b ...
Research Article Impact Factor: 4.226 ISSN: 2319-507X
Research Article Impact Factor: 4.226 ISSN: 2319-507X

Soft Computing: Constituent and Applications of Soft
Soft Computing: Constituent and Applications of Soft

... In the soft computing framework, the basic idea which has been developed so far has consisted in supposing that there is a set of resolving agents which are basically algorithms for solving combinatorial optimization problems, and to execute them cooperatively by means of a coordinating agent to sol ...
Fuzzy Expert Control Systems: Knowledge Base Validation
Fuzzy Expert Control Systems: Knowledge Base Validation

... fuzzy controllers, originated from a logic of “vague” and “imprecise” concepts, are used in most cases to approximate precise, deterministic controller functions, thus contradicting some of the principles that ground the usefulness of fuzzy logic. ...
Lecture 1 Introduction to knowledge
Lecture 1 Introduction to knowledge

... Some people are smarter in some ways than others. Sometimes we make very intelligent decisions but sometimes we also make very silly mistakes. Some of us deal with complex mathematical and engineering problems but are moronic in philosophy and history. Some people are good at making money, while oth ...
Slide - ICT@UP
Slide - ICT@UP

Intelligence
Intelligence

... One of the most ambitious projects of the era of great expectations was the General Problem Solver (GPS). Allen Newell and Herbert Simon from the Carnegie Mellon University developed a general-purpose program to simulate humansolving methods. Newell and Simon postulated that a problem to be solved c ...
Concept Analysis Diagram
Concept Analysis Diagram

... Sub-Concepts are teaching points regarding the Concept being defined thus just a line is printed between the Concept and Sub-Concepts. The need for Nursing Care is triggered by: Compromised Antecedent(s), Decreased quality of Attribute(s), Negative Consequence(s), and/or a potentially negative impac ...
IOSR Journal of Computer Engineering (IOSR-JCE)
IOSR Journal of Computer Engineering (IOSR-JCE)

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Click Here For

...  Review of the latest technology available to design robotic systems.  Use of professional engineering tools to design robots.  Programming of microcontrollers to control a robotic system.  Hands-on experience to design a robotic system. Learning Outcome:  Students will be able to design a robo ...
Artificial Intelligence Winter 2004
Artificial Intelligence Winter 2004

... character and a model to which one can refer refer. The informal notion than has a formal original. E.g. “high fever” has as original a certain precise temperature (which may not be known or may not be of interest).  In a subjective situation there is no exact original (like “this is stupid”), only ...
comparison of purity and entropy of k-means
comparison of purity and entropy of k-means

On the Characteristic Functions of Fuzzy Systems 1 Introduction 2
On the Characteristic Functions of Fuzzy Systems 1 Introduction 2

... The approximation properties of fuzzy logic systems with defuzzification have been extensively studied starting in the 1990s [6] (Teodorescu 1990), [1] [2], [3], [7]. However, while somewhat elementary, the properties that guarantee that these systems have derivable or continuous input-output functio ...
What is Logic?
What is Logic?

...  “If There exists an x for which P holds, then it is not true that for all x P does not hold”. ...
Survey on Remotely Sensed Image Classification
Survey on Remotely Sensed Image Classification

... maximization clustering algorithm and self-organizing maps algorithm. All these algorithms are evaluated as per the following factors: number of clusters, size of dataset, type of dataset and type of software used. FSVM is used to enhance the SVM in reducing the effect of outliers and noises in data ...
On Elkan`s theorems: Clarifying their meaning
On Elkan`s theorems: Clarifying their meaning

... omitted from the first version of Elkan’s theorem. As to the rest of the assumptions, both t~A ∧ B! ⫽ min$t~A!, t~B!% and t~¬A! ⫽ 1 ⫺ t~A! are quite reasonable and, in fact, are often used in applications of fuzzy logic. Let us now concentrate on the last assumption, that is, on t~A! ⫽ t~B! if A and ...
Week11 - Information Management and Systems
Week11 - Information Management and Systems

... the chromosome selection and formulate the problem effectively.  Thus genetic algorithms should be considered at present more as an instrument for scientific research rather than as a tool for generic practical data analysis, for instance, in finance. ...
Knowledge-Driven Business Intelligence Systems: Part II
Knowledge-Driven Business Intelligence Systems: Part II

... chromosome selection and formulate the problem effectively. ƒ Thus genetic algorithms should be considered at present more as an instrument for scientific research rather than as a tool for generic practical data analysis, for instance, in finance. ...
Chapter 7 Propositional and Predicate Logic
Chapter 7 Propositional and Predicate Logic

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PowerPoint 簡報
PowerPoint 簡報

On the Notion of Coherence in Fuzzy Answer Set Semantics
On the Notion of Coherence in Fuzzy Answer Set Semantics

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intro_to_ai. ppt

... Do experts understand the system? (have a model) Do experts expect to understand the system? (readability) ...
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Fuzzy concept

A fuzzy concept is a concept of which the boundaries of application can vary considerably according to context or conditions, instead of being fixed once and for all. This means the concept is vague in some way, lacking a fixed, precise meaning, without however being unclear or meaningless altogether. It has a definite meaning, which can become more precise only through further elaboration and specification, including a closer definition of the context in which the concept is used. A fuzzy concept is understood by scientists as a concept which is ""to an extent applicable"" in a situation, and it therefore implies gradations of meaning. The best known example of a fuzzy concept around the world is an amber traffic light, and indeed fuzzy concepts are nowadays widely used in traffic control systems.The Nordic myth of Loki's wager suggests that concepts which lack a precise meaning or precise boundaries of application cannot be usefully discussed at all. However, the idea of ""fuzzy concepts"" proposes that ""somewhat vague terms"" can be operated with, since we can explicate and define the variability of their application, by assigning numbers to it.
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