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Distributed fuzzy case based reasoning

Santanu Chaudhury, Tuhina Singh, Partha S Goswami
2004 Applied Soft Computing  
This paper presents a framework for a distributed knowledge based system by integrating case based reasoning (CBR) and Fuzzy Logic.  ...  The framework for handling distributed case bases enables our system to construct solution based on collective experience distributed by discipline, time, and geography.  ...  Conclusions We have proposed a distributed fuzzy case based reasoning architecture.  ... 
doi:10.1016/j.asoc.2003.10.003 fatcat:zui5u3fag5gqfcdd6k2voiyvmm

Use of Fuzzy Histograms to Model the Spatial Distribution of Objects in Case-Based Reasoning [chapter]

Alan Davoust, Michael W. Floyd, Babak Esfandiari
Advances in Artificial Intelligence  
We present our implementation of this approach in a case-based reasoning project, and experimental results showing highly efficient scene comparison.  ...  In the context of the RoboCup Simulation League, we describe a new representation of a software agent's visual perception ("scene"), well suited for case-based reasoning.  ...  highly suitable for case-based reasoning.  ... 
doi:10.1007/978-3-540-68825-9_8 dblp:conf/ai/DavoustFE08 fatcat:ibsdzqblezapnahpdxjhpmbyte

A new approach to fuzzy reasoning

J. Weisbrod
1998 Soft Computing - A Fusion of Foundations, Methodologies and Applications  
For a fuzzy rule base, that maximizes completeness at the cost of consistency, we derive a new type of inference called {reasoning.  ...  In this paper we present a new theory for fuzzy reasoning. This theory is twofold. In general, a fuzzy rule base is both partially inconsistent and partially incomplete.  ...  Acknowledgements The author wants to thank Martin Spott for many exciting and fruitful discussions and his excellent work on possibility distributions.  ... 
doi:10.1007/s005000050037 fatcat:cm4jnorqxzbuvin67iwntce73m

The Fuzzy Knowledge Representation in a First Logic

2017 Annals of Dunarea de Jos University. Fascicle I : Economics and Applied Informatics  
The first order predicates languages facilitate rigorously expressing complex knowledge, imposing appropriate reasoning techniques.  ...  The goal of this paper is to provide an extended framework for fuzzy knowledge representation and processing, used in a prototype system CFK.  ...  Like for the classical case, the fuzzy pattern-matching aims to determine the sets of instances of the reasons.  ... 
doaj:a3bfcdc8b81743ef9a60851264e4bc70 fatcat:vuve2dk72jea7fx4dyf5dl3d7u

An Integrated Knowledge Management System

Vasile Mazilescu
2014 Annals of Dunarea de Jos University. Fascicle I : Economics and Applied Informatics  
The aim of this paper is to present a Knowledge Management System based on Fuzzy Logic (FLKMS), a real-time expert system to meet the challenges of the dynamic environment.  ...  , using a knowledge model for control, embedded within the expert system's operational knowledge base.  ...  The reasoning specific to this agent is performed by the inference engine based on fuzzy logic.  ... 
doaj:4e29318b13494a2cb155cc2378cde74d fatcat:qf2up3cuqrenje7prgj4pfygjy

Reliability Assessment of Distribution System Using Fuzzy Logic for Modelling of Transformer and Line Uncertainties [article]

Ahmad Shokrollahi, Hossein Sangrody, Mahdi Motalleb, Mandana Rezaeiahari, Elham Foruzan, Fattah Hassanzadeh
2017 arXiv   pre-print
Reliability assessment of distribution system, based on historical data and probabilistic methods, leads to an unreliable estimation of reliability indices since the data for the distribution components  ...  In this paper, the ENS index along with other commonly used indices in reliability assessment are evaluated for the distribution system using fuzzy logic.  ...  reasons.  ... 
arXiv:1707.04506v1 fatcat:yr3lofir2rd45fnbauulqdp4gm

A Fuzzy Non-linear Similarity Measure for Case-Based Reasoning Systems for Radiotherapy Treatment Planning [chapter]

Rupa Jagannathan, Sanja Petrovic, Angela McKenna, Louise Newton
2010 IFIP Advances in Information and Communication Technology  
We propose to capture this experience by using case-based reasoning.  ...  Central to the working of our case-based reasoning system is a novel similarity measure that takes into account the non-linear effect of the individual case attributes on the similarity measure.  ...  Case-based reasoning (CBR) is based on the concept that the solution of a problem can be derived from the solutions of similar problems [1] .  ... 
doi:10.1007/978-3-642-16239-8_17 fatcat:dijgb5avhraano6mhb2dssa5sq

Reasoning about Unmodelled Concepts - Incorporating Class Taxonomies in Probabilistic Relational Models [article]

Daniel Nyga, Michael Beetz
2015 arXiv   pre-print
knowledge base.  ...  We show that by exploiting this structure, probability distributions can be represented more compactly and that the reasoning systems become capable of reasoning about concepts not contained in the probabilistic  ...  The key idea of FUZZY-MLNs is to learn joint probability distributions conditioned on large taxonomic knowledge bases that are assumed to be given as factual knowledge.  ... 
arXiv:1504.05411v1 fatcat:qoo4wqqdkjexbaunryq2go4vrm

Reasoning over decomposing fuzzy description logic

Mohamed Gasmi, Mustapha Bourahla
2016 Journal of Innovation in Digital Ecosystems  
Ontology Description logic Fuzzy logic Automatic inference and reasoning A B S T R A C T A DF-ALC (Decomposing fuzzy ALC) is proposed in this paper to satisfy the need for representing and reasoning with  ...  A DF-ALC is also proposed to satisfy the need for seeing the necessity of decomposing ontology into several sub-ontologies in order to optimize the fuzzy reasoning process.  ...  The tableau algorithm will be applied in the local ontologies before merged into the reasoning parallel case or propagated in the reasoning distributed case.  ... 
doi:10.1016/j.jides.2016.05.003 fatcat:bmdpbfdujnbrdbt77kcy76spom

Approximate Arithmetic Operations of U-numbers

R.A. Aliev
2016 Procedia Computer Science  
Thus, usuality is a special case of a Z-number where second component is "usually", and is referred to as U-number. Humans mainly use U-numbers in everyday reasoning.  ...  Formally, it is handled by possibilistic-probabilistic constraint, where A is a fuzzy restriction on a value of a random variable X, and "usually" is a fuzzy restriction on a value of probability measure  ...  Approximate reasoning is based on fuzzy logic 22, 23 and has found a lot of successful applications in various fields 24, 25 .  ... 
doi:10.1016/j.procs.2016.09.370 fatcat:hta4ik3ezjhxvf3xwdyasxbkpi

Page 1838 of Mathematical Reviews Vol. , Issue 94d [page]

1994 Mathematical Reviews  
Summary: “Rule-based fuzzy approximate reasoning uses vari- ous techniques of modified modus ponens. The observation is in most cases not identical with any of the antecedents in the rules.  ...  First, the two probabilistic fuzzy sets coming from the raw data are built when consider- ing complementary cumulative distribution functions. Then, fuzzy reasoning on inference rules is considered.  ... 


Vasile Mazilescu
2015 Risk in Contemporary Economy  
The aim of this paper is to provide a formalism for fuzzy rule bases, included in our prototype system FUZZY_ENTERPRISE.  ...  The language of the first-degree predicates facilitates the formulation of complex knowledge in a rigorous way, imposing appropriate reasoning techniques.  ...  All the fuzzy constants used in knowledge representation and modelling, for the synthesis of fuzzy reasoning algorithms, are represented by trapezoidal possibility distributions, such as g ≤ d, ϕ, δ ≥  ... 
doaj:38c8d1a371e8429eb938122bcef9fca1 fatcat:gtqhi6gnfrcwfgmsdfh66uek6y

A possibilistic-logic-based approach to integrating imprecise and uncertain information

Jonathan Lee, Kevin F.R. Liu, Weiling Chiang
2000 Fuzzy sets and systems (Print)  
An inference mechanism for fuzzy propositions with fuzzy truth values is developed to serve as a bridge that brings together the possibilistic reasoning and fuzzy reasoning into a hybrid approach to reasoning  ...  A reasoning mechanism capable of dealing with imprecise and uncertain information is essential for expert systems.  ...  Obviously, Ogawa's extension was not based on the fuzzy reasoning but on the uncertain reasoning.  ... 
doi:10.1016/s0165-0114(98)00039-6 fatcat:bdycbxoyrrejjotgs5rbq6zgzq

Practical use of fuzzy implicative gradual rules in knowledge representation and comparison with Mamdani rules

Hazaël Jones, Serge Guillaume, Brigitte Charnomordic, Didier Dubois
2005 European Society for Fuzzy Logic and Technology  
The comparison is carried out with regard to the output possibility distribution, the crisp inferred value and the rule base consistency.  ...  Nevertheless, fuzzy implicative rules, and especially gradual rules, provide another kind of knowledge representation, which can be very useful in approximate reasoning.  ...  Fuzzy logic based decision support tools have an intrinsic explanatory power. It can be a very good reason for using them preferably to other techniques, when interpretability is at stake.  ... 
dblp:conf/eusflat/JonesGCD05 fatcat:cnap5m23argzbe6c2sguiji2wq

Problems and Prospects in Fuzzy Data Analysis [chapter]

Rudolf Kruse, Christian Borgelt, Detlef Nauck
2000 Lecture Notes in Computer Science  
Since the aim of fuzzy technology has always been to model linguistic information and to achieve understandable solutions, we expect it to play an important role in information mining.  ...  In this case the rule base is seen as prior knowledge and the tuned rule base is posterior knowledge.  ...  For this reason recently possibilistic graphical models also gained some attention [8] , for which learning algorithms have been developed in analogy to the probabilistic case.  ... 
doi:10.1007/10720181_4 fatcat:4b4he3jsorgaxmsmdavojhctiy
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