Main description:

Provides strong and accessible theoretical bases to swarm intelligence algorithms, from particle optimization to bioinspired and meta-heuristic algorithms

Presents emerging meta-heuristic algorithms and applications

Provides overviews on Python and R based computing libraries for swarm intelligence and meta-heuristic algorithms

Presenting real-world applications, especially on Industry, Medicine and Biology.

Contents:

SECTION 1: FUNDAMENTALS AND ADVANCEMENTS ON SWARM INTELLIGENCE 1. Swarm Intelligence Based Algorithm for Feature Selection in High-Dimensional Datasets 2. Swarm Intelligence for Data Mining 3. Leveraging Center-Based Sampling Theory for Enhancing Particle Swarm Classification of Textual Data 4. Reinforcement Learning for Out-of-the-box Parameter Control for Evolutionary and Swarm-based Algorithm SECTION 2: APPLICATIONS 5. Recognition of Emotions in the Elderly Through Audio Signal Analysis 6. Recognition of Emotions in the Elderly through Facial Expressions: A Machine Learning-Based Approach 7. Identification of Emotion Parameters in Music to Modulate Human Affective States 8. Clinical Decision Support in the Care of Symptomatic Patients with COVID-19: An Approach Based on Machine Learning and Swarm Intelligence 9. The Sound of the Mind: Detection of Common Mental Disorders Using Vocal Acoustic Analysis and Machine Learning