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Different Methodologies in Treating Uncertainty

Areeg Abdalla
2019 Zenodo  
Uncertainty is unavoidable when dealing with data.  ...  The errors in measurements, limitations of measuring tools, or imprecise definition of linguistic variables may result in different types of uncertainty.  ...  Reasoning based on fuzzy propositions is referred to as approximate reasoning. The fundamental components of approximate reasoning are these "IF-THEN" fuzzy propositions [9] .  ... 
doi:10.5281/zenodo.3050652 fatcat:u5unupjy2rfhfjponene6uuqdi

A Review of Soft Computing Solutions to Intrusion in Computer Network

Gargee Shukla, Anamika Shukla, Hari Shankar
2016 International Journal of Computer Applications  
Artificial Neural Networks (ANN), Fuzzy Logic theory (FL) and Genetic Algorithm (GA) represent the most common tools of soft computing.  ...  The capability of soft computing tools to tolerate imprecision, partial truth, uncertainty and ability to provide low solution costs to real world problems and computationally intelligent problems are  ...  Fuzzy Logic is a tool for applying reasoning and uncertainty tolerance. It is a kind of "multi-valued logic".  ... 
doi:10.5120/ijca2016911644 fatcat:w3y4vn5jv5gedfmsmidmoh3jg4

What does fuzzy logic bring to AI?

Didier Dubois, Henri Prade
1995 ACM Computing Surveys  
In classification problems the use of fuzzy classes obvi- ates the need for arbitrarily classifying borderline cases at the beginning of a reasoning stage.  ...  Encoding Similarity and Interpolation In the mid-70's, when MYCIN was be- coming a landmark among rule-based ex- pert systems dealing with uncertainty, the first fuzzy rule-based system was  ... 
doi:10.1145/212094.212115 fatcat:yjfii6oc3rc4jlnem24odgdxci

Fuzzy Expert Systems (FES) for Medical Diagnosis

Smita SushilSikchi, Sushil Sikchi, Ali M. S.
2013 International Journal of Computer Applications  
Fuzzy logic has proved to be the remarkable tool for building intelligent decision making systems based on the expert's knowledge and observations.  ...  of Fuzzy Expert Systems in Medical Diagnosis, Methodologies and Modelling of Fuzzy Expert Systems, Neuro-Fuzzy Approaches, Fuzzy Expert System Shells and Frameworks.  ...  Fuzzy logic presents powerful reasoning methods that can handle uncertainties and vagueness.  ... 
doi:10.5120/10508-5466 fatcat:5qhkgux4djfklkn6soiwf5htva

Risk Analysis using Fuzzy System based Risk Matrix Methodology

Magdy Zaky
2018 Arab Journal of Nuclear Sciences and Applications  
Fuzzy logic is one of the intelligence systems and it has wide range applications in fault analysis, event classification, accident analysis, safety and risk assessment.  ...  Applications of the fuzzy system involves analyzing and managing the risk in nuclear reactors based on the classification of the events information.  ...  Fuzzy Logic System The Fuzzy Logic system is a mathematical tool for dealing with uncertainty, introduced by Professor L. A.  ... 
doi:10.21608/ajnsa.2018.2448.1047 fatcat:zbsmmwsho5appdlfsw6d6rasfi

Case-Based Reasoning: Concepts, Features and Soft Computing

Simon C.K. Shiu, Sankar K. Pal
2004 Applied intelligence (Boston)  
Here we first describe the concepts, components and features of CBR. The feasibility and merits of using CBR for problem solving is then explained.  ...  This is followed by a description of the relevance of soft computing tools to CBR.  ...  Using Fuzzy Logic. Fuzzy set theory has been successfully applied to computing with words [6] or the matching of linguistic terms for reasoning.  ... 
doi:10.1023/b:apin.0000043556.29968.81 fatcat:7hn3di5fuzgdlh523un75daf3u

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

1994 Mathematical Reviews  
Fuzzy logic provides a systematic basis for representing and infer- ring with this kind of knowledge.  ...  Reason. 9 (1993), no. 2, 139-164. Summary: “The management of uncertainty and imprecision is becoming more and more important in knowledge-based systems.  ... 

Detecting and resolving spatial ambiguity in text using named entity extraction and self learning fuzzy logic techniques [article]

Kanagavalli V R, Raja. K
2013 arXiv   pre-print
This paper proposes a method for detecting the presence of spatial uncertainty in the text and dealing with spatial ambiguity using named entity extraction techniques coupled with self learning fuzzy logic  ...  A word which can belong to one or more classes and which has a level of uncertainty in it can be best handled by a self learning Fuzzy Logic Technique.  ...  Fuzzy logic provides a foundation for the development of new tools for dealing with natural languages and knowledge representation, such as precipitated natural language, theory of hierarchical definability  ... 
arXiv:1303.0445v1 fatcat:6wsfyzfwtjbz5fvbch4t5wxque

Use of Fuzzy Set Theory in Environmental Engineering Applications: A Review

Arif Khan
2017 International Journal of Engineering Research and Applications  
It takes advantage of advanced computational intelligence techniques such as fuzzy sets and logic, for quantifying and manipulating in a mathematically rigorous way, subjective, inherently uncertain or  ...  Methods of solving the identified environmental problems, considering mathematical rigorous alternative assessment of environmental component process using fuzzy logic and approximate reasoning, are described  ...  with an index model for quality evaluation of surface water quality classification using fuzzy logic.  ... 
doi:10.9790/9622-0706020106 fatcat:qght2px5dbcx5gaxnkpfjjgnha

Fuzzy Optimization Model for post harvest selection process of Pecan (Carya illinoinensis)

The paper aims to evaluate the application of fuzzy logic in the evaluation and classification of the selection of pecans in the post harvest process using tests and instruments that determine their best  ...  Fuzzy logic has proven to be very effective with matlab/simulink to develop and simulate the entire system, through an appropriate choice of rules and membership functions and applying the Mamdani method  ...  Diffuse Logic: Basically, Diffuse Logic is a multivariate logic that allows to represent mathematically uncertainty and vagueness, providing formal tools for its treatment.  ... 
doi:10.35940/ijitee.l1082.10812s219 fatcat:fvkcbswbdbg2jas5a4khrvuvsq

Analyzing Agricultural Crop Production and their Uncertainty Using Linear Regression and Fuzzy Logic

Om Prakash Singh, Bijay Kumar Mandal, Sunil Kumar
2021 IARJSET  
The randomness deals with general uncertainties while fuzzy logic suitable for the complex phenomena. The statistical regression methodology is used traditionally for such complex predictions.  ...  The proposed approach framework consists of fuzzy logic based controller-Fig1, Fuzzy Linear regression-Fig2 and Framework-Fig3.  ...  It helps in expressing an uncertainty about tangible meaning of used labels and tolerates soft constraints and flexible requirements. It is also the tool for reasoning.  ... 
doi:10.17148/iarjset.2021.8855 fatcat:ghes6dm3zbanlb2bkrvibsh7k4

Combining Fuzzy Logic and Dempster-Shafer Theory

Andino Maseleno, Md. Mahmud Hasan, Norjaidi Tuah
2015 TELKOMNIKA Indonesian Journal of Electrical Engineering  
Integrating Fuzzy Logic and Dempster-Shafer theory by calculating the similarity between Fuzzy membership function.  ...  This research aims to combine the mathematical theory of evidence with the rule based logics to refine the predictable output.  ...  Integration within symbolic, rule-based models have been used for control and classification purposes [2, 3] .  ... 
doi:10.11591/tijee.v16i3.1651 fatcat:fx5yav3mc5h7fkntbbl4zznpvm

Fuzzy Logic, Soft Computing, and Applications [chapter]

Inma P. Cabrera, Pablo Cordero, Manuel Ojeda-Aciego
2009 Lecture Notes in Computer Science  
We survey on the theoretical and practical developments of the theory of fuzzy logic and soft computing.  ...  Specifically, we briefly review the history and main milestones of fuzzy logic (in the wide sense), the more recent development of soft computing, and finalise by presenting a panoramic view of applications  ...  Extended tools for fuzzy and similarity-based reasoning.  ... 
doi:10.1007/978-3-642-02478-8_30 fatcat:6asrztozdve6rju4dh3467ypxm

Unification Of Randomized Anomaly In Deception Detection Using Fuzzy Logic Under Uncertainty

S. Rajkumar, V. Narayani, Dr. S.P. Victor
2012 International Journal of Research in Computer Science  
We propose a research model which comprises Fuzzy logic, Uncertainty and Randomization.  ...  Identifying Deception in any mode of communication is a tedious process without using the proper tool for detecting those vulnerabilities.  ...  Enviornment Information Sharing System Test for uncertainty Implementing Randomization technique Combining Uncertainty & Fuzzy Logic Applying Fuzzy Logic Combining Uncertainty, Fuzzy Logic  ... 
doi:10.7815/ijorcs.22.2012.016 fatcat:zaj66epe3jhf5nsxnzkdqigiqa

An overview on the roles of fuzzy set techniques in big data processing: Trends, challenges and opportunities

Hai Wang, Zeshui Xu, Witold Pedrycz
2017 Knowledge-Based Systems  
Fuzzy sets have been employed for big data processing due to their abilities to represent and quantify aspects of uncertainty.  ...  We stress that some more sophisticated augmentations of fuzzy sets and their integrations with other tools could offer a novel promising processing environment.  ...  Acknowledgments The authors would like to thank the Editor-in-Chief and four anonymous reviewers for their insightful and constructive commendations that have led to an improved version of this paper.  ... 
doi:10.1016/j.knosys.2016.11.008 fatcat:i2ay7ugn5rfkhmz7jw6hyc67fm
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