Proceedings of the Eighth International Conference on Soft Computing and Pattern Recognition (SoCPaR 2016)

1. Auflage 2018
ISBN: 978-3-319-60617-0
Verlag: Springer International Publishing

Buch, Englisch, Band 614, 733 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 11227 g

Reihe: Advances in Intelligent Systems and Computing

This volume presents 70 carefully selected papers from a major joint event: the 8th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2016) and the 8th International Conference on Computational Aspects of Social Networks (CASoN 2016). SoCPaR–CASoN 2016, which was organized by the Machine Intelligence Research Labs (MIR Labs), USA and Vellore Institute of Technology (VIT), India and held at the VIT on December 19–21, 2016. It brings together researchers and practitioners from academia and industry to share their experiences and exchange new ideas on all interdisciplinary areas of soft computing and pattern recognition, as well as intelligent methods applied to social networks.
This book is a valuable resource for practicing engineers/scientists and researchers working in the field of soft computing, pattern recognition and social networks.

Zielgruppe

Research

Autoren/Hrsg.

Abraham, Ajith

Muda, Azah Kamilah

Cherukuri, Aswani Kumar

Madureira, Ana Maria

Fachgebiete

• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Social Media, Semantic Web, Web 2.0
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Fuzzy-Systeme
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Mustererkennung, Biometrik

Inhaltsverzeichnis

Sensitivity analysis on effect of biomechanical factors for classifying vertebral deformities.- Smart Manufacturing through Sensor Based Efficiency monitoring system.- A New Form of Fuzzy Reasoning Tool to Ensure both Accuracy and Readability.- Predicting Mobile Application Ratings using Artificial Neural Network.- A Comparative Analysis of the different Data Mining Tools by using Supervised Learning Algorithms.- Security Enabled Cluster Head Selection for Wireless Sensor Network using Improved Firefly Optimization.