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Fuzzy adaptive resonance theory approach to supplier involvement in product development: a case study in Turkish automobile industry

Ozkan, Coskun; Akman, Gulsen; Keskin, Gulsen Aydin; … - In: European Journal of Industrial Engineering 5 (2011) 1, pp. 43-63

problems, a clustering approach – fuzzy adaptive resonance theory (Fuzzy ART) – is used. The proposed methodology is explained …

Persistent link: https://www.econbiz.de/10009352919

Methods for Extracting Knowledge

Stancu, Ana-Maria Ramona; Dragut, Bogdanel Marian; … - In: Knowledge Horizons - Economics 5 (2013) 2, pp. 201-204

classification, regression and clustering. In terms of classification, it describes some of the techniques and methods, namely the … decision trees, the Bayesian method, k-NN, etc. The steps of a process solving clustering and the K-means algorithm used are …

Persistent link: https://www.econbiz.de/10010700137

Theory Forms in Unemployment

BUGUDUI, Elena; CIOBANU, Ghenadie - In: Romanian Statistical Review Supplement 60 (2012) 2, pp. 120-125

This article aims to develop a group of Romanian counties, using classification techniques forms uncontrolled, depending on several variables that affect unemployment, with Ward's algorithm and distance Cebashev type and complete aggregation technique. The approach aims to establish common...

Persistent link: https://www.econbiz.de/10010596237

World Search Engine IQ Test Based on the Internet IQ Evaluation Algorithms

Liu, Feng; Shi, Yong; Wang, Bo - In: International Journal of Information Technology & … 14 (2015) 02, pp. 221-237

With increasing concern about Internet intelligence, this paper proposes concepts of the Internet and Internet subsystem IQs over search engines. Based on human IQ calculations, the paper first establishes a 2014 Internet Intelligence Scale and designs an intelligence test bank regarding search...

Persistent link: https://www.econbiz.de/10011279040

A new approach to classification

Fuentes-Garcia, R.; Walker, S. G. - In: Journal of Applied Statistics 37 (2010) 1, pp. 137-146

Clustering is a common and important issue, and finite mixture models based on the normal distribution are frequently …

Persistent link: https://www.econbiz.de/10008582914

Unsupervised and supervised data classification via nonsmooth and global optimization

Bagirov, A.; Rubinov, A.; Soukhoroukova, N.; Yearwood, J. - In: TOP: An Official Journal of the Spanish Society of … 11 (2003) 1, pp. 1-75

Persistent link: https://www.econbiz.de/10005371426

Clustering employees on the basis of their perception from critical success factors of total quality management and its influence on customer focus

Gavareshki, Mohammad Hosein Karimi; Dabestani, Reza; … - In: International journal of management concepts and … 12 (2019) 2, pp. 103-116

Persistent link: https://www.econbiz.de/10012105427

Impact of application of data mining in the Lebanese banking sector

Kalakech, Kamel Hassan; El-Mousawi, Hasan Y. - In: International journal of economics and finance 11 (2019) 8, pp. 101-116

Persistent link: https://www.econbiz.de/10012106002

An empirical study on customer risk management in banking industry : applying k-means and RFM methods (evidence form two Iranian private banks)

Farughi, Hiwa; Alaniazar, Seiran; Mousavipour, Seyedhamed - In: International journal of risk assessment and management … 19 (2016) 4, pp. 315-330

Persistent link: https://www.econbiz.de/10011658565

A new comparative model for national innovation systems based on machine learning classification techniques

Alnafrah, Ibrahim; Zeno, Bassel - In: Innovation and development : RIAD 10 (2020) 1, pp. 45-66

Persistent link: https://www.econbiz.de/10012174915