The modified fuzzy art and a two-stage clustering approach to cell design

DOI10.1016/j.ins.2007.06.027zbMath1122.68499OpenAlexW2038858601MaRDI QIDQ2456490

Tülin Aktin, Rıfat Gürcan Özdemir, Gunes Gencyilmaz

Publication date: 18 October 2007

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2007.06.027

zbMATH Keywords

clusteringartificial neural networkgroup technologyIntelligent manufacturingmachine cell formation

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Uses Software

• MOCACEF

Cites Work

• An effective learning of neural network by using RFBP learning algorithm
• An improved neural network leader algorithm for part-machine grouping in group technology
• Supervised learning on a fuzzy Petri net
• Multi-objective optimization of manufacturing cell design
• An ideal seed non-hierarchical clustering algorithm for cellular manufacturing
• ZODIAC—an algorithm for concurrent formation of part-families and machine-cells
• A massively parallel architecture for a self-organizing neural pattern recognition machine
• Machine-component cell formation in group technology: a neural network approach
• FACT: A new neural network-based clustering algorithm for group technology
• Performance of Fuzzy ART neural network for group technology cell formation
• Performance of Fuzzy ART neural network and hierarchical clustering for part-machine grouping based on operation sequences
• Sequence-dependent clustering of parts and machines: A Fuzzy ART neural network approach
• MOCACEF 1.0: Multiple objective capability based approach to form part-machine groups for cellular manufacturing applications
• Fuzzy sets
• Unnamed Item

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