Bio-Inspired Algorithms for Data Streaming and Visualization, Big Data Management, and Fog Computing

Book Overview

Chapter 1. The Big Data Approach Using Bio-Inspired Algorithms: Data Imputation.- Chapter 2. Parameter Tuning onto Recurrent Neural Network and Long Short Term Memory (RNN-LSTM) Network for Feature Selection in Classification of High-dimensional Bioinformatics Datasets.- Chapter 3. Data Stream Mining in Fog Computing Environment with Feature Selection Using Ensemble of Swarm Search Algorithms.- Chapter 4. Pattern Mining Algorithms.- Chapter 5. Extracting Association Rules: Meta-Heuristic and Closeness Preference Approach.- Chapter 6. Lightweight Classifier-based Outlier Detection Algorithms from Multivariate Data Stream.- Chapter 7. Comparison of Contemporary Meta-heuristic Algorithms for Solving Economic Load Dispatch Problem.- Chapter 8. The paradigm on fog computing with bio-inspired search methods and the '5Vs' of big data.- Chapter 9. Approach for sentiment analysis on social media sites.- Chapter 10. Data Visualisation techniques and Algorithms.- Chapter 11. Business Intelligence.- Chapter 12. Big Data Tools for Tasks.

• Format: Paperback
• Language: English
• ISBN: 9811566976
• ISBN13: 9789811566974
• Release Date: August 2021
• Publisher: Springer
• Length: 226 Pages
• Weight: 0.75 lbs.
• Dimensions: 0.5" x 6.1" x 9.2"