Hybrid Intelligent Systems
17th International Conference on Hybrid Intelligent Systems (HIS 2017) held in Delhi, India, December 14-16, 2017
1st Edition
Published on 15. March 2018
XIV, 354 pages
978-3-319-76351-4 (ISBN)
Description
This book includes recent research on Hybrid Intelligent Systems. It presents 35 selected papers from the 17th edition of the International Conference on Hybrid Intelligent Systems (HIS), which was held in Delhi, India from December 14 to 16, 2017. Reflecting the awareness in the respective academic communities that combined approaches are essential to solving the remaining tough problems in computational intelligence, the HIS is a premier conference focused on the hybridization of intelligent systems. The book offers a valuable reference guide for all researchers, students and practitioners in the fields of Computer Science and Engineering.
More details
Series
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Product notice
Reflowable
Illustrations
XIV, 354 p. 139 illus.
File size
48,32 MB
ISBN-13
978-3-319-76351-4 (9783319763514)
DOI
10.1007/978-3-319-76351-4
Schweitzer Classification
Other editions
Additional editions
Ajith Abraham | Pranab Kr. Muhuri | Azah Kamilah Muda
Hybrid Intelligent Systems
17th International Conference on Hybrid Intelligent Systems (HIS 2017) held in Delhi, India, December 14-16, 2017
Book
03/2018
Springer
€160.49
Shipment within 10-15 days
Content
Neural Tree for Estimating the Uniaxial Compressive Strength of Rock Materials.- Fault Tolerant Multiple Synchronized Parallel Load Balancing in Cloud.- Semi-Supervised Learning with the Integration of Fuzzy Clustering and Artificial Neural Network.- GMM-KNN: A Method for Processing Continuous k-NN Queries Based on The Gaussian Mixture Model.- Edge Detection for Cement Images Based on Interactive Genetic Algorithm.- A Fast Satellite Image Super-Resolution Technique Using Multicore Processing.- Use of Cellular Automata to Predict Deforestation in Queretaro.- A Classification Algorithm for Assessing the Quality Criteria for Business Process Models.
