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An Extension of the Fuzzy Possibilistic Clustering Algorithm Using Type-2 Fuzzy Logic Techniques

Elid Rubio, Oscar Castillo, Fevrier Valdez, Patricia Melin, Claudia I. Gonzalez, Gabriela Martinez
2017 Advances in Fuzzy Systems  
In this work an extension of the Fuzzy Possibilistic C-Means (FPCM) algorithm using Type-2 Fuzzy Logic Techniques is presented, and this is done in order to improve the efficiency of FPCM algorithm.  ...  With the purpose of observing the performance of the proposal against the Interval Type-2 Fuzzy C-Means algorithm, several experiments were made using both algorithms with well-known datasets, such as  ...  Competing Interests The authors declare that there is no conflict of interests regarding the publication of this paper.  ... 
doi:10.1155/2017/7094046 fatcat:rrljhzbqcvaydikvptdu27o3a4

Interval Type-2 Fuzzy Possibilistic C-Means Clustering Algorithm [chapter]

E. Rubio, Oscar Castillo, Patricia Melin
2016 Studies in Fuzziness and Soft Computing  
In this paper, we present the extension of the fuzzy possibilistic C-means (FPCM) algorithm using type-2 fuzzy logic techniques, with the goal of improving the performance of this algorithm.  ...  We also performed the comparison of this proposed algorithm against the interval type-2 fuzzy C-means (IT2FCM) algorithm to observe whether the proposed approach performs better than this algorithm.  ...  Interval Type-2 Fuzzy Possibilistic C-Means Algorithm The interval type-2 FPCM algorithm is a proposed extension of the FPCM algorithm using type-2 fuzzy logic techniques.  ... 
doi:10.1007/978-3-319-32229-2_14 fatcat:4sn2uu7pebai7pbyrcyj3s6upa

An Efficient Segmentation and Classification System in Medical Images Using Intuitionist Possibilistic Fuzzy C-Mean Clustering and Fuzzy SVM Algorithm

Chiranji Lal Chowdhary, Mohit Mittal, Kumaresan P., P. A. Pattanaik, Zbigniew Marszalek
2020 Sensors  
The IPFCM improves the fundamentals of fuzzy c-mean by using intuitionist fuzzy sets.  ...  Intuitionist fuzzy c-mean (IFCM) and possibilistic fuzzy c-mean (PFCM) algorithms are hybridised to deal with problems of fuzzy c-mean.  ...  For the detection of cancer in an image, we applied the existing segmentation techniques such as the Otsu algorithm, FCM (fuzzy c-mean) clustering, IFCM (ntuitionist fuzzy c-mean) clustering, and PFCM  ... 
doi:10.3390/s20143903 pmid:32668793 fatcat:o3s3sgwnsfhy5agtukhkbuk5km

Extracting fuzzy classifications rules from three-way data

Janusz Kacprzyk, Jan Owsinski, Dimitri Viattchenin
2014 Journal of Automation, Mobile Robotics & Intelligent Systems  
A novel technique based on a heuristic method of possibilistic clustering is proposed.  ...  A description of basic concepts of a heuristic method of possibilistic clustering based on concept of an allotment is provided. A preprocessing technique for three-way data is shown.  ...  Acknowledgements The research has been partially supported, first, by the National Centre of \science  ... 
doi:10.14313/jamris_2-2014/19 fatcat:4as4vs5hbfbtbcg3wvwwurakyq

How to process uncertainty in machine learning?

Barbara Hammer, Thomas Villmann
2007 The European Symposium on Artificial Neural Networks  
, in particular fuzzy-clustering on the one side and fuzzy inference systems on the other side.  ...  The aim of this paper is to motivate the merits and problems when dealing with uncertainty in machine learning and to give an overview about methodologies which fall under the framework of neurofuzzy methods  ...  In [36] possibilistic clustering as a controlled mixture of the proposal of Krishnapuram/Keller and the basic algorithm is investigated.  ... 
dblp:conf/esann/HammerV07 fatcat:l6w7jly2jvejvfsxdhtzdxniiq

A Fuzzy-Possibilistic Fuzzy Ruled Clustering Algorithm for RBFNNs Design [chapter]

A. Guillén, I. Rojas, J. González, H. Pomares, L. J. Herrera, A. Prieto
2006 Lecture Notes in Computer Science  
be approximated and the fuzzy-possibilistic partition of the data.  ...  The algorithm also introduces a fuzzy logic element by setting a fuzzy rule that determines the input vectors that influence each center position, this fuzzy rule considers the output of the function to  ...  It is based on a mixed fuzzy-possibilistic supervised approach that, with the use of fuzzy logic and problem specific knowledge, will provide an adequate placement of the centers.  ... 
doi:10.1007/11908029_67 fatcat:qyh7snc35zeixayv67wgqmffbq

Robust Kernel Clustering Algorithm for Nonlinear System Identification

Mohamed Bouzbida, Lassad Hassine, Abdelkader Chaari
2017 Mathematical Problems in Engineering  
Our proposed algorithm called Robust Kernel Possibilistic Fuzzy C-Means (RKPFCM) algorithm is an extension of the PFCM algorithm based on kernel method, where the Euclidean distance used the robust hyper  ...  To identify the parameters of Takagi-Sugeno fuzzy model several clustering algorithms are developed such as the Fuzzy C-Means (FCM) algorithm, Possibilistic C-Means (PCM) algorithm, and Possibilistic Fuzzy  ...  Our algorithm is an improvement of the Possibilistic Fuzzy -Means Clustering (PFCM) where we used a hyper tangent kernel function to calculate the distance of data point from the cluster centers and a  ... 
doi:10.1155/2017/2427309 fatcat:sbw7dgfxufgmnb5aggklwklubq

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

Om Prakash Singh, Bijay Kumar Mandal, Sunil Kumar
2021 IARJSET  
The present works focus on investigation of various used machine learning algorithms for their suitability in crop yields perdition and finally proposed an approach based on linear regression and fuzzy  ...  The proposed approach framework consists of fuzzy logic based controller-Fig1, Fuzzy Linear regression-Fig2 and Framework-Fig3.  ...  Zadeh, 1965] proposed the fuzzy logic as an extension of binary logic founded on fuzzy set theory. It is a many value logic that deals with situations where boundaries are not well determined.  ... 
doi:10.17148/iarjset.2021.8855 fatcat:ghes6dm3zbanlb2bkrvibsh7k4

The posterity of Zadeh's 50-year-old paper

James C. Bezdek, Didier Dubois, Henri Prade
2015 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)  
OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible.  ...  This is an author-deposited version published in : Eprints ID : 15501 The contribution was presented at :  ...  Keller, "A possibilistic approach to clustering", TFS, 1(2), 1993, 98-110.  ... 
doi:10.1109/fuzz-ieee.2015.7337858 dblp:conf/fuzzIEEE/BezdekDP15 fatcat:jeydd2agx5eppps2bpy5z32mcm

Hybrid Fuzzy n Possibilistic Clustering Model based on Genetic Optimization: Case Study on Brain Tissues of Patients with Alzheimer's Disease

Lilia Lazli, Mounir Boukadoum
2018 International Journal of Networked and Distributed Computing (IJNDC)  
center partition. (2) Genetic algorithms (GA) to achieve optimization and to determine the appropriate cluster centers and the fuzzy corresponding partition matrix. (3) Possibilistic C-Means (PCM) algorithm  ...  Brain tissue segmentation is one of the most important parts of clinical diagnostic tools. Fuzzy C-mean (FCM) is one of the most popular clustering based segmentation methods.  ...  The problem of fuzzy clustering has been posed as an optimization problem. So, we used GA to give cluster centers.  ... 
doi:10.2991/ijndc.2018.6.2.2 fatcat:upd5pts2kndmbn6tjybmmfyj44

The legacy of 50 years of fuzzy sets: A discussion

Didier Dubois, Henri Prade
2015 Fuzzy sets and systems (Print)  
The discussion is organized on the basis of three potential understanding of the grades of membership to a fuzzy set, depending on what the fuzzy set intends to represent: a group of elements with borderline  ...  OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible.  ...  However, if a type 2 fuzzy set is understood as a fuzzy set of (a possibility distribution over) membership functions, it is enough to apply the extension principle to the type 1 fuzzy logic expression  ... 
doi:10.1016/j.fss.2015.09.004 fatcat:yqsjyfemjfhyzoqthwumsbiok4

A Computer-Aided Type-II Fuzzy Image Processing for Diagnosis of Meniscus Tear

M. H. Fazel Zarandi, A. Khadangi, F. Karimi, I. B. Turksen
2016 Journal of digital imaging  
The scheme of the proposed type-2 fuzzy image processing model is composed of three distinct modules: Pre-processing, Segmentation, and Classification. λ-nhancement algorithm is used to perform the pre-processing  ...  For the segmentation step, first, Interval Type-2 Fuzzy C-Means (IT2FCM) is applied to the images, outputs of which a re then employed by Interval Type-2 Possibilistic C-Means (IT2PCM) to perform post-processes  ...  Type-2 fuzzy sets were first introduced by Zadeh as an extension of type-I fuzzy sets [25] .  ... 
doi:10.1007/s10278-016-9884-y pmid:27198133 pmcid:PMC5114228 fatcat:nucotzdoozhtpdszlklpv7t22e

Web mining: a survey in the fuzzy framework

Dragos Arotaritei, Sushmita Mitra
2004 Fuzzy sets and systems (Print)  
A hybridization of fuzzy sets with genetic algorithms (another soft computing tool) is described for information retrieval. An extensive bibliography is also included.  ...  The role of fuzzy sets in handling the di erent types of uncertainties/impreciseness is highlighted.  ...  According to Zadeh [35] , fuzzy logic may serve as the backbone of the Semantic Web, an extension of the current Web in which information is given well-deÿned meaning, thereby better enabling computers  ... 
doi:10.1016/j.fss.2004.03.003 fatcat:xtnbbibicjh73g7av34nm2acoy

From Fuzzy Clustering to a Fuzzy Rule-Based Fault Classification Model

Enrico Zio, Piero Baraldi, Irina Crenguta Popescu
2008 International Journal of Computational Intelligence Systems  
In this work, a methodology is developed for transforming an opaque, fuzzy clustering-based classification model into a fuzzy logic model based on transparent linguistic rules.  ...  These are obtained by cluster projection with appropriate coverage and distinguishability constraints onto the fuzzy input partitioning interface.  ...  Acknowledgements The authors wish to thank Drs. Paolo Fantoni and Davide Roverso of the IFE, Halden Reactor Project for providing the transient simulation data. Nomenclature BWR  ... 
doi:10.1080/18756891.2008.9727605 fatcat:dxaxsw6lxfgp7h5ryfblc3ufeq

A New Type-2 Fuzzy Algorithm for Unmanned Aerial Vehicle Image Segmentation

Tingyu Zhong, Wenping Liu, Youqing Luo, Chih-Cheng Hung
2017 International Journal of Multimedia and Ubiquitous Engineering  
This paper proposes a new type-2 fuzzy algorithm for the Unmanned Aerial Vehicle (UAV) image segmentation.  ...  The proposed method achieves better segmentation results than those of the K-means, FCM clustering algorithms and possibilistic c-means algorithm (PCM) in our comparative study for UAV images.  ...  Besides, the intuitionistic type-2 fuzzy set has been formed as an extension of intuitionistic fuzzy set for handling uncertainty.  ... 
doi:10.14257/ijmue.2017.12.5.07 fatcat:ng4j2s7ncncjbicuy6yxqtvjby
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