Innovations in Fuzzy Clustering Theory and Applications /
Sato-Ilic, Mika.
Innovations in Fuzzy Clustering Theory and Applications / [electronic resource] : by Mika Sato-Ilic, Lakhmi C. Jain. - XIII, 151 p. online resource. - Studies in Fuzziness and Soft Computing, 205 1434-9922 ; . - Studies in Fuzziness and Soft Computing, 205 .
to Fuzzy Clustering -- Fuzzy Clustering based Principal Component Analysis -- Fuzzy Clustering based Regression Analysis -- Kernel based Fuzzy Clustering -- Evaluation of Fuzzy Clustering -- Self-Organized Fuzzy Clustering.
ZDB-2-ENG
There is a great interest in clustering techniques due to the vast amount of data generated in every field including business, health, science, engineering, aerospace, management and so on. It is essential to extract useful information from the data. Clustering techniques are widely used in pattern recognition and related applications. The research monograph presents the most recent advances in fuzzy clustering techniques and their applications. The following contents are included: Introduction to Fuzzy Clustering Fuzzy Clustering based Principal Component Analysis Fuzzy Clustering based Regression Analysis Kernel based Fuzzy Clustering Evaluation of Fuzzy Clustering Self-Organized Fuzzy Clustering This book is directed to the computer scientists, engineers, scientists, professors and students of engineering, science, computer science, business, management, avionics and related disciplines.
9783540343578
10.1007/3-540-34357-1 doi
Engineering.
Artificial intelligence.
Engineering mathematics.
Engineering.
Appl.Mathematics/Computational Methods of Engineering.
Artificial Intelligence (incl. Robotics).
TA329-348 TA640-643
519
Innovations in Fuzzy Clustering Theory and Applications / [electronic resource] : by Mika Sato-Ilic, Lakhmi C. Jain. - XIII, 151 p. online resource. - Studies in Fuzziness and Soft Computing, 205 1434-9922 ; . - Studies in Fuzziness and Soft Computing, 205 .
to Fuzzy Clustering -- Fuzzy Clustering based Principal Component Analysis -- Fuzzy Clustering based Regression Analysis -- Kernel based Fuzzy Clustering -- Evaluation of Fuzzy Clustering -- Self-Organized Fuzzy Clustering.
ZDB-2-ENG
There is a great interest in clustering techniques due to the vast amount of data generated in every field including business, health, science, engineering, aerospace, management and so on. It is essential to extract useful information from the data. Clustering techniques are widely used in pattern recognition and related applications. The research monograph presents the most recent advances in fuzzy clustering techniques and their applications. The following contents are included: Introduction to Fuzzy Clustering Fuzzy Clustering based Principal Component Analysis Fuzzy Clustering based Regression Analysis Kernel based Fuzzy Clustering Evaluation of Fuzzy Clustering Self-Organized Fuzzy Clustering This book is directed to the computer scientists, engineers, scientists, professors and students of engineering, science, computer science, business, management, avionics and related disciplines.
9783540343578
10.1007/3-540-34357-1 doi
Engineering.
Artificial intelligence.
Engineering mathematics.
Engineering.
Appl.Mathematics/Computational Methods of Engineering.
Artificial Intelligence (incl. Robotics).
TA329-348 TA640-643
519