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Journal of Systems and Software:: A Fuzzy Neural Network for
Journal of Systems and Software:: A Fuzzy Neural Network for

... ©2009-2011 AJSS Journal. All rights reserved http://www.scientific‐journals.org  ...
Introduction to Neuro-fuzzy and Soft computing
Introduction to Neuro-fuzzy and Soft computing

...  Fuzzy logic allows making definite decisions based on imprecise or ambiguous data  ANN tries to incorporate human thinking process to solve problems without mathematically modeling them.  Both these methods can be used to solve nonlinear problems, and problems that are not properly specified, bu ...
CS2053
CS2053

... Content beyond syllabus covered (if any): MATLAB simulation of fuzzy systems, Ref. 9 ...
The use of Fuzzy Logic for Artificial Intelligence in Games
The use of Fuzzy Logic for Artificial Intelligence in Games

... wealth of examples that can be found in game AI manuals [21, 6]. Bayesian networks are used in Real-Time Strategy games (RTS) for goal planning [21]. Neural networks appear in the Creatures game series1 as well as in several realtime strategy games and in the award-winning game Black & White2 . More ...
Feature Selection Using Fuzzy Objective Functions
Feature Selection Using Fuzzy Objective Functions

A Partitioned Fuzzy ARTMAP Implementation for Fast Processing of
A Partitioned Fuzzy ARTMAP Implementation for Fast Processing of

... handling large databases is the family of ART neural networks. This family of neural networks is considerably faster than the backpropagation neural network architecture, one of the most popular neural network models. Furthermore, ART neural networks have the added advantage over the backpropagation ...
sv-lncs - ISIS2013
sv-lncs - ISIS2013

... exact boundary of several states. Other research use physiological sensors to recognize the user’s context, as the user’s body status can represent the user’s activity and also the user’s emotion which depends on the activity. Therefore using the physiological sensor with accelerometers will help t ...
492-166 - wseas.us
492-166 - wseas.us

... This paper presents a model specific for medical diagnosis developed with Neurofuzzy techniques based on Radial Basis Functions (RBF) network. The model provides a user-friendly interface, to the experts in the medical domain with the possibility to design diagnostic applications without deep backgr ...
Which Truth Values in Fuzzy Logics Are De nable?
Which Truth Values in Fuzzy Logics Are De nable?

Computational Intelligence and Active Networks
Computational Intelligence and Active Networks

... to stall on the standardization process), protocol bridged (that translates between different revisions/generations of a service as in the active bridge), and most importantly, services themselves: users are free to customize the network infrastructure to fit their needs, when such needs emerge. Thi ...
AAAI Proceedings Template
AAAI Proceedings Template

... classification and generalising; they are also able to predict events in the future on the basis of history [Mena, 2003]. These abilities may be useful for forensics, where they can be used to collect evidence after a crime has been committed. However, ANNs have four algorithms which can be helpful ...
Computational Intelligence in Data Mining
Computational Intelligence in Data Mining

... ∪ operators represent the intersection and union of fuzzy sets, respectively. S is a symmetric measure in [0,1]. If S(Ai,j , Al,j ) = 1, then the two membership functions Ai,j and Al,j are equal. S(Ai,j , Al,j ) becomes 0 when the membership functions are non-overlapping. The complete rule base simp ...
decisions making in design process – examples of artificial
decisions making in design process – examples of artificial

... enable its continuum. Automatism of the design process can be achieved by application of the artificial intelligence methods. Faculty of Mechanical Engineering in Niš is working on development of intelligent integrated system for design of power transmitters. During this work, various expert and fuz ...
Rule Insertion and Rule Extraction from Evolving Fuzzy
Rule Insertion and Rule Extraction from Evolving Fuzzy

... rules as an initialization procedure thus allowing for existing information to be used prior to the evolving process (the rule insertion procedure for FuNNs can be applied [6, 14]). If initially there are no rule (case) nodes connected to the fuzzy input and fuzzy output neurons with non-zero connec ...
An introduction to artificial intelligence applications in petroleum
An introduction to artificial intelligence applications in petroleum

... neural network is suggested in order to determine reservoir properties from well logs. Fuzzy curve analysis based on fuzzy logics is used for selecting the best-related well logs with core porosity and permeability data. Artificial neural network is used as a nonlinear regression method to develop t ...
چند نمومه تمرین - Hassan Saneifar Professional Page
چند نمومه تمرین - Hassan Saneifar Professional Page

Neural Network
Neural Network

PPT - LSDIS
PPT - LSDIS

... theoretically, we could translate all the expressions of the DL into L2 and then use resolution or some algorithm as a decision procedure. However, it is generally the case that Tableau algorithms are computationally less expensive. ...
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PDF

Improving Construction and Maintenance of Agent-based
Improving Construction and Maintenance of Agent-based

Adaptive Fuzzy Clustering of Data With Gaps
Adaptive Fuzzy Clustering of Data With Gaps

... Mining and Exploratory Data Analysis. Conventional approach to solving these problems requires that each observation may belong to only one cluster. There are many situations when a feature vector with different levels of probabilities or possibilities can belong to several classes. This situation i ...
ICAISC 2004 Preliminary Program
ICAISC 2004 Preliminary Program

Neural Networks
Neural Networks

... An Artificial Neural Network (ANN) is an information processing paradigm that is inspired by the biological nervous systems, such as the human brain’s information processing mechanism. The key element of this paradigm is the novel structure of the information processing system. It is composed of a l ...
Knowledge acquisition and processing: new methods for
Knowledge acquisition and processing: new methods for

Fuzzy Logic and Neural Nets
Fuzzy Logic and Neural Nets

... (weighted) average of its possible values – Center of Mass: Take all the rules we partially believe, and take their weighted average ...
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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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