Fuzzy clustering method and evaluation based on multi criteria ...

[PDF] Fuzzy clustering method and evaluation based on multi ...

The proposed algorithm is used as a pre-processing method for data followed by Gustafson-Kessel (GK) algorithm to classify credit scoring data and revealed ...

Fuzzy clustering method and evaluation based on multi criteria decision making technique ... In the financial sector, credit scoring is one of the most successful ...

Fuzzy clustering method and evaluation based on multi criteria ...

Sameer, Fadhaa Othman (2018) Fuzzy clustering method and evaluation based on multi criteria decision making technique. Doctoral thesis, Universiti Putra ...

A Novel Multi-view Fuzzy Clustering Algorithm Based on Fuzzy C ...

Based on this, we propose a fuzzy assessment method to evaluate the fuzziness of the clustering results and mark the objects between the ...

Multi-criteria evaluation method for fuzzy interval measure and ...

Fuzzy clustering is an effective method for multi-criteria decision making (MCDM). In this paper, an approach for utilizing fuzzy cluster with interval ...

Description: Fuzzy clustering method and evaluation based on multi ...

Fuzzy clustering method and evaluation based on multi criteria decision making technique. In the financial sector, credit scoring is one of the most ...

Fuzzy c-means clustering-based key performance indicator design ...

... multi-criteria decision methods were generally used in these studies. In this study, a fuzzy c-means clustering (FCM) based KPI is designed to evaluate the ...

Multicriteria Ordered the Profile Clustering Algorithm Based on ...

To address the problem of finding ranking in clusters based on multicriteria in the fuzzy environment, we propose a multicriteria ordered ...

OWA-based multi-criteria decision making based on fuzzy methods

In order to sort the alternatives, i.e. Academic Programmes, two methods of average ranks and hierarchical clustering are used. The sorted ...

Data analysis with fuzzy clustering methods - ScienceDirect.com

Approaches that are based on a global criteria for optimality of clustering results are presented in Section 4.1. These algorithms minimize the objective ...

(PDF) Integration model of Fuzzy C means clustering algorithm and ...

Fuzzy Analytical Hierarchy Process was utilized to calculate the weight of RFM variables. Then, based on the weighted RFM values, Fuzzy c-means ...

Integration of Fuzzy C-Means Clustering and TOPSIS ... - IEEE Xplore

Because the process is used for multi-criteria data, the best membership value based on the results of cluster sub-criteria to get the weight of TOPSIS. A good ...

Coupling Fuzzy Multi-Criteria Decision-Making and Clustering ...

In this study, a coupled fuzzy Multi-Criteria Decision-Making (MCDM) approach was employed to site landfills in Lanzhou, a semi-arid valley basin city in China.

Generalized trajectory fuzzy clustering based on the multi-objective ...

In order to improve the clustering results of the classical algorithm, the optimization methods such as genetic algorithm and particle swarm optimization [15] ...

ML | Fuzzy Clustering - GeeksforGeeks

Fuzzy clustering is a type of clustering algorithm in machine learning that allows a data point to belong to more than one cluster with different degrees of ...

Detecting subject-specific activations using fuzzy clustering - PMC

In this context, we present a new approach based on the classification of all voxels according to the clustering principle of fuzzy logic (Zadeh, 1965). Fuzzy ...

An agent-oriented decision support system combining fuzzy ... - UAEH

Hence, to enhance group decision making, we developed a solu- tion based on the combination of Multi-Agent Systems, the fuzzy. C-means clustering technique and ...

A novel approach for fuzzy clustering based on neutrosophic ...

Semantic Scholar extracted view of "A novel approach for fuzzy clustering based on neutrosophic association matrix" by H. Long et al.

Combination Evaluation Method of Fuzzy C-Mean Clustering ...

Therefore, a hybrid weighted combination evaluation method based on fuzzy C-means (FCM) clustering validity functions was proposed. The ...

Component-wise design method of fuzzy C-means clustering validity ...

Wang L, Cui G, Cai X (2023) Fuzzy clustering optimal k selection method based on multi-objective optimization. · Hartigan JA, Wong MA (1979) Algorithm AS 136: a ...