Recent Advances on Soft Computing and Data Mining

Proceedings of the Third International Conference on Soft Computing and Data Mining (SCDM 2018), Johor, Malaysia, February 06-07, 2018
Herausgegeben:Ghazali, Rozaida; Deris, Mustafa Mat; Nawi, Nazri Mohd; Abawajy, Jemal H.

• Broschiertes Buch

Produktbeschreibung

This book offers a systematic overview of the concepts and practical techniques that readers need to get the most out of their large-scale data mining projects and research studies. It guides them through the data-analytical thinking essential to extract useful information and obtain commercial value from the data. Presenting the outcomes of International Conference on Soft Computing and Data Mining (SCDM-2017), held in Johor, Malaysia on February 6-8, 2018, it provides a well-balanced integration of soft computing and data mining techniques. The two constituents are brought together in various combinations of applications and practices. To thrive in these data-driven ecosystems, researchers, engineers, data analysts, practitioners, and managers must understand the design choice and options of soft computing and data mining techniques, and as such this book is a valuable resource, helping readers solve complex benchmark problems and better appreciate the concepts, tools, and techniquesemployed.

Produktdetails

• Advances in Intelligent Systems and Computing 700
• Verlag: Springer / Springer International Publishing / Springer, Berlin
• Artikelnr. des Verlages: 978-3-319-72549-9
• 1st ed. 2018
• Seitenzahl: 544
• Erscheinungstermin: 12. Januar 2018
• Englisch
• Abmessung: 235mm x 155mm x 30mm
• Gewicht: 822g
• ISBN-13: 9783319725499
• ISBN-10: 3319725491
• Artikelnr.: 49841334

Inhaltsangabe

An Improved Hybrid Firefly Algorithm for Solving Optimization Problems.- Classification of JPEG Files by Using Extreme Learning Machine.- A Relative Tolerance Relation of Rough Set for Incomplete Information Systems.- An Algorithm Design of Kansei Recommender System.- A Framework to Cluster Temporal Data Using Personalised Modelling Approach.- Fibonacci Polynomials Based Functional Link Neural Network for Classification Tasks.