Natural Computing for Unsupervised Learning (Unsupervised and Semi-Supervised Learning)
ISBN-10: 3319985655
ISBN-13: 9783319985657
Edition 版次: 1st ed. 2019
Publication Date 出版日期: 2018-11-01
Print Length 页数: 273 pages
This book highlights recent research advances in unsupervised learning using natural computing techniques such as artificial neural networks,evolutionary algorithms,swarm intelligence,artificial immune systems,artificial life,quantum computing,DNA computing,and others. The book also includes information on the use of natural computing techniques for unsupervised learning tasks. It features several trending topics,such as big data scalability,wireless network analysis,engineering optimization,social media,and complex network analytics. It shows how these applications have triggered a number of new natural computing techniques to improve the performance of unsupervised learning methods. With this book,the readers can easily capture new advances in this area with systematic understanding of the scope in depth. Readers can rapidly explore new methods and new applications at the junction between natural computing and unsupervised learning.
Includes advances on unsupervised learning using natural computing techniques
Reports on topics in emerging areas such as evolutionary multi-objective unsupervised learning
Features natural computing techniques such as evolutionary multi-objective algorithms and many-objective swarm intelligence algorithms
Part l.Advances in Natural Computing
1.Detailed Modeling of CSC-STATCOM with Optimized PSO Based Controller
2.A Brief Review and Comparative Study of Nature-Inspired Optimization Algorithms Applied to Power System Control
3.Self-Organization: A Perspective on Applications in the Internet of Things
Partll.Advances in Unsupervised Learning
4.Applications of Unsupervised Techniques for Clustering of Audio Data
5.Feature Extraction and Classification in Brain-Computer Interfacing: Future Research lssues and Challenges
6.A Multilingual Framework for a Question Answering System for the Support of Ticket Data: An Extended Approach
Part ll.Natural Computing for Unsupervised Learning
7.Chemical Reaction-Based Optimization Algorithm for Solving Clustering Problems
8.A Novel Artificial Bee Colony Algorithm for Robust Permutation Flowshop Scheduling
9.Semantic lmage Retrieval Using Point-Set Topology and the Ant Sleeping Model
10.Filter-Based Feature Selection Methods Using Hil Climbing Approach
Part IV.Others
11.Social Networking Awareness in Indian Higher Education
Natural Computing for Unsupervised Learning
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