1st Edition
Swarm Intelligence Trends and Applications
This book presents the fundamentals of swarm intelligence, from classic algorithms to emerging techniques. It presents comprehensive theoretical foundations and examples using the main Computational Intelligence methods in programming languages such as Python, Java and MATLAB®. Real-world applications are also presented in areas as diverse as Medicine, Biology and industrial applications.
The book is organized into two parts. The first part provides an introduction to swarming algorithms and hybrid techniques. In the second part, real world applications of swarm intelligence are presented to illustrate how swarm algorithms can be used in applications of optimization and pattern recognition, reviewing the principal methods and methodologies in swarm intelligence.
SECTION 1: FUNDAMENTALS AND ADVANCEMENTS ON SWARM INTELLIGENCE
1. Swarm Intelligence Based Algorithm for Feature Selection in High-Dimensional Datasets
Nandini Nayar, Sachin Ahuja, and Shaily Jain
2. Swarm Intelligence for Data Mining
Razieh Sheikhpour
3. Leveraging Center-Based Sampling Theory for Enhancing Particle Swarm Classification of Textual Data
Anwar Ali Yahya
4. Reinforcement Learning for Out-of-the-box Parameter Control for Evolutionary and Swarm-based Algorithm
Marcelo Gomes Pereira de Lacerda
SECTION 2: APPLICATIONS
5. Recognition of Emotions in the Elderly Through Audio Signal Analysis
Flávio S. Fonseca, Arianne S. Torcate, Maíra A. Santana, Juliana C. Gomes, Nicole Charron, José Daniel S. do Carmo, Giselle M. M. Moreno and Wellington P. dos Santos
6. Recognition of Emotions in the Elderly through Facial Expressions: A Machine Learning-Based Approach
Arianne Sarmento Torcate, Maíra Araújo Santana, Juliana Carneiro Gomes, Ingrid Bruno Nunes, Flávio Secco Fonseca, Gisele M. M. Moreno, and Wellington Pinheiro dos Santos
7. Identification of Emotion Parameters in Music to Modulate Human Affective States
Maíra A. Santana, Ingrid B. Nunes, Andressa L. Q. Ribeiro, Flávio S. Fonseca, Arianne S. Torcate, Amanda Suarez, Vanessa Marques, Nathália Córdula, Juliana C. Gomes, Giselle M. M. Moreno, and Wellington P. Santos
8. Clinical Decision Support in the Care of Symptomatic Patients with COVID-19: An Approach Based on Machine Learning and Swarm Intelligence
Ingrid Bruno Nunes, Pedro Vitor Soares Gomes de Lima, Andressa Laysa Queiroz Ribeiro, Leandro Ferreira Frade Soares, Maria Eduarda da Silva Santana, Maria Luysa Teles Barcelar, Juliana Carneiro Gomes, Clarisse Lins de Lima, Maíra Araújo de Santana, Rodrigo Gomes de Souza, Valter Augusto de Freitas Barbosa, Ricardo Emmanuel de Souza, and Wellington Pinheiro dos Santos
9. The Sound of the Mind: Detection of Common Mental Disorders Using Vocal Acoustic Analysis and Machine Learning
Caroline Wanderley Espinola, Juliana Carneiro Gomes, Jessiane Mônica Silva Pereira and Wellington P. Santos
Biography
Wellington Pinheiro dos Santos is an Associate Professor at the Department of Biomedical Engineering at the Federal University of Pernambuco (UFPE), Brazil. He is a DSc in Electrical Engineering at the Federal University of Campina Grande (UFCG, 2009), and a MSc (2003) and BSc (2001) in Electrical and Computer Engineering at UFPE, Brazil. His main research interests are pattern recognition, machine learning, intelligent diagnosis systems, evolutionary computing, applied neuroscience, and artificial intelligence in health.
Juliana Carneiro Gomes is a Biomedical Engineer from the Federal University of Pernambuco (UFPE, 2016), with a sandwich period at Mercer University, USA. She worked as a researcher at the Advanced Imaging Algorithms and Instrumentation Laboratory at Johns Hopkins University, USA. She is a Master in Biomedical Engineering (UFPE, 2019) and a PhD student in Computer Engineering at the University of Pernambuco (UPE). She is a Professor at the Physics Department at UFPE.
Valter Augusto de Freitas Barbosa has a PhD in Mechanical Engineering (2022), a Master in Biomedical Engineering (2017) and a Biomedical Engineer from the Federal University of Pernambuco (2014), Brazil, with a sandwich period at the Université de Technologie de Compiègne, France. He is currently an Assistant Professor at the Federal Rural University of Pernambuco. His research interests are focused on pattern recognition, artificial intelligence and deep neural networks.
