Bio-Inspired Algorithms for Data Streaming and Visualization, Big Data Management, and Fog Computing
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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.
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Details
- ISBN-13: 9789811566974
- ISBN-10: 9811566976
- Publisher: Springer
- Publish Date: August 2021
- Dimensions: 9.21 x 6.14 x 0.5 inches
- Shipping Weight: 0.75 pounds
- Page Count: 226
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