Results 31 to 40 of about 152,595 (295)
A new fuzzy set merging technique using inclusion-based fuzzy clustering [PDF]
, 2008 This paper proposes a new method of merging parameterized fuzzy sets based on clustering in the parameters space, taking into account the degree of inclusion of each fuzzy set in the cluster prototypes.
Kaymak, U, Nefti-Meziani, S, Oussalah, M
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TOWARDS FINDING A NEW KERNELIZED FUZZY C-MEANS CLUSTERING ALGORITHM [PDF]
Journal of Process Management and New Technologies, 2014 Kernelized Fuzzy C-Means clustering technique is an attempt to improve the performance of the conventional Fuzzy C-Means clustering technique. Recently this technique where a kernel-induced distance function is used as a similarity measure instead ...
Samarjit Das, Hemanta K. Baruah
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General fuzzy min-max neural network for clustering and classification [PDF]
, 2000 This paper describes a general fuzzy min-max (GFMM) neural network which is a generalization and extension of the fuzzy min-max clustering and classification algorithms of Simpson (1992, 1993).
Bargiela, Andrzej, Gabrys, Bogdan
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ANALISIS PERBANDINGAN METODE FUZZY C-MEANS DAN SUBTRACTIVE FUZZY C-MEANS
Media Statistika, 2015 Fuzzy C-Means (FCM) is one of the most frequently used clustering method. However FCM has some disadvantages such as number of clusters to be prespecified and partition matrix to be randomly initiated which makes clustering result becomes inconsistent ...
Baiq Nurul Haqiqi, Robert Kurniawan
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BigFCM: Fast, Precise and Scalable FCM on Hadoop
, 2016 Clustering plays an important role in mining big data both as a modeling technique and a preprocessing step in many data mining process implementations.
Ghadiri, Nasser +2 more
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Automatic generation of fuzzy classification rules using granulation-based adaptive clustering [PDF]
, 2015 A central problem of fuzzy modelling is the generation of fuzzy rules that fit the data to the highest possible extent. In this study, we present a method for automatic generation of fuzzy rules from data. The main advantage of the proposed method is its
Abbod, MF, Al-Shammaa, M
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Assessment of Heart Disease using Fuzzy Classification Techniques
The Scientific World Journal, 2001 In this paper we discuss the classification results of cardiac patients of ischemical cardiopathy, valvular heart disease, and arterial hypertension, based on 19 characteristics (descriptors) including ECHO data, effort testings, and age and weight.
Horia F. Pop, Tudor L. Pop, Costel Sarbu
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Chemical Engineering Transactions, 2017 In this paper, the author research on electrical equipment’s fault diagnosis based on the improved support vector machine and fuzzy clustering. Combining the support vector combined fuzzy sets and neural network to carry on the fault diagnosis is a most ...
Yuling Yan
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Fuzzy clustering of fuzzy systems [PDF]
2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583), 2005 A fuzzy system entirely characterizes one region of the input-output product space S = U /spl times/ V through a relation expressed by a set of fuzzy rules. Effectively, the fuzzy system establishes a fuzzy map, which assigns for each input fuzzy set in U an output fuzzy set in V.
Salgado, Paulo, Garrido, Paulo
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 In the process of land cover segmentation from remote sensing image, there are some uncertainties such as “significant difference in class density”, “different objects with same spectrum”, and “same object with ...
Chengmao Wu, Xiaokang Guo
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